อ้างอิง:
adjunct_island
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/adjunct_island')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_gender_agreement
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/anaphor_gender_agreement')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
anaphor_number_agreement
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/anaphor_number_agreement')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
animate_subject_passive
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_passive')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
animate_subject_trans
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_trans')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
เป็นสาเหตุ
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/causative')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
complex_NP_island
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/complex_NP_island')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
พิกัด_โครงสร้าง_ข้อจำกัด_ซับซ้อน_ซ้าย_สาขา
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_complex_left_branch')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
พิกัด_โครงสร้าง_ข้อ จำกัด_วัตถุ_สกัด
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_object_extraction')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_irregular_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_irregular_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_with_adj_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_with_adj_irregular_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_with_adj_irregular_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ตัวกำหนด_noun_agreement_with_adjective_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adjective_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
วอกแวก_ข้อตกลง_สัมพันธ์_คำนาม
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relational_noun')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ฟุ้งซ่าน_agreement_relative_clause
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relative_clause')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
drop_argument
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/drop_argument')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
จุดไข่ปลา_n_bar_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
จุดไข่ปลา_n_bar_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ดำรงอยู่_there_object_raising
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/existential_there_object_raising')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ดำรงอยู่_มี_ปริมาณ_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ดำรงอยู่_มี_ปริมาณ_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ดำรงอยู่_there_subject_raising
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/existential_there_subject_raising')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
คำสบถ_it_object_raising
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/expletive_it_object_raising')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
น่าสนใจ
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/inchoative')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
อกรรมกริยา
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/intransitive')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ไม่สม่ำเสมอ_past_participle_adjectives
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_adjectives')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ไม่สม่ำเสมอ_past_participle_verbs
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_verbs')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ไม่สม่ำเสมอ_plural_subject_verb_agreement_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
ไม่สม่ำเสมอ_plural_subject_verb_agreement_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_echo_question
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_echo_question')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
left_branch_island_simple_question
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_simple_question')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
matrix_question_npi_licensor_present
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/matrix_question_npi_licensor_present')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/npi_present_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
npi_present_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/npi_present_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
only_npi_licensor_present
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/only_npi_licensor_present')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
only_npi_scope
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/only_npi_scope')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
เฉยๆ_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/passive_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
พาสซีฟ_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/passive_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_c_command
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_c_command')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_case_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_case_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_โดเมน_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_โดเมน_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_โดเมน_3
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_3')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
หลักการ_A_การสร้างใหม่
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/principle_A_reconstruction')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Regular_plural_subject_verb_agreement_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
Regular_plural_subject_verb_agreement_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_negation_npi_licensor_present
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_licensor_present')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_negation_npi_scope
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_scope')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
sentential_subject_island
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/sentential_subject_island')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
สุดยอด_ปริมาณ_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
สุดยอด_ปริมาณ_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
แกร่ง_vs_raising_1
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_1')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
แกร่ง_vs_raising_2
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_2')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
สกรรมกริยา
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/transitive')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_เกาะ
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_island')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_object_gap
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_object_gap')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_questions_subject_gap_long_distance
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap_long_distance')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_no_gap_long_distance
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap_long_distance')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}
wh_vs_that_with_gap_long_distance
ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap_long_distance')
- คำอธิบาย :
BLiMP is a challenge set for evaluating what language models (LMs) know about
major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each
containing 1000 minimal pairs isolating specific contrasts in syntax,
morphology, or semantics. The data is automatically generated according to
expert-crafted grammars.
- ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
- เวอร์ชั่น : 0.1.0
- แยก :
| แยก | ตัวอย่าง |
|---|---|
'train' | 1,000 |
- คุณสมบัติ :
{
"sentence_good": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"sentence_bad": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"field": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"linguistics_term": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"UID": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"simple_LM_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"one_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"two_prefix_method": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"lexically_identical": {
"dtype": "bool",
"id": null,
"_type": "Value"
},
"pair_id": {
"dtype": "int32",
"id": null,
"_type": "Value"
}
}