הפניות:
אי ספיח
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/adjunct_island')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/anaphor_gender_agreement')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/anaphor_number_agreement')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_passive')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/animate_subject_trans')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
סִבָּתִי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/causative')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
מורכב_NP_אי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/complex_NP_island')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
coordinate_structure_constraint_complex_left_branch
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_complex_left_branch')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
חילוץ_חפץ_אילוץ_קואורדינטה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/coordinate_structure_constraint_object_extraction')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_לא סדיר_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_לא סדיר_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_irregular_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_הסכם_עם_התאמה_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_עם_adj_irregular_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_עם_adj_irregular_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adj_irregular_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קובע_שם_שם_הסכם_עם_תואר_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/determiner_noun_agreement_with_adjective_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
שם עצם_יחס_מסיח_הסכמה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relational_noun')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
סעיף_יחס_הסכם_מסיח
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/distractor_agreement_relative_clause')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
טיפ_טיעון
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/drop_argument')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
ellipsis_n_bar_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
ellipsis_n_bar_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/ellipsis_n_bar_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
הרמת_אובייקט_קיומית
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/existential_there_object_raising')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
כמות_יש_קיומית_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קיומיים_יש_כמתים_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/existential_there_quantifiers_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
העלאת_נושא_קיומית_שם
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/existential_there_subject_raising')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
העלאת_חפץ_זה_העלאת_חומר
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/expletive_it_object_raising')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
אינכואטיבי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/inchoative')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
בלתי טרנזיטיבי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/intransitive')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
שמות תואר_חלקי עבר לא רגילים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_adjectives')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
פעלים_חלק_עבר לא סדירים
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/irregular_past_participle_verbs')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
irregular_plural_subject_verb_agreement_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
irregular_plural_subject_verb_agreement_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/irregular_plural_subject_verb_agreement_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
שמאל_ענף_אי_הד_שאלה
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_echo_question')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
שאלה_פשוטה_הענף_שמאלי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/left_branch_island_simple_question')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/matrix_question_npi_licensor_present')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/npi_present_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/npi_present_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/only_npi_licensor_present')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/only_npi_scope')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
פסיבי_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/passive_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
פסיבי_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/passive_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
princip_A_c_command
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_c_command')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
עיקרון_מקרה_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
עיקרון_מקרה_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_case_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
princip_A_domain_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
princip_A_domain_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
princip_A_domain_3
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_domain_3')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
עיקרון_א_שחזור
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/principle_A_reconstruction')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/regular_plural_subject_verb_agreement_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_licensor_present')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/sentential_negation_npi_scope')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
האי_נושא_משפטי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/sentential_subject_island')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
superlative_quantifiers_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
superlative_quantifiers_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/superlative_quantifiers_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קשה_מול_העלאה_1
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_1')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
קשה_מול_העלאה_2
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/tough_vs_raising_2')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
טרנזיטיבי
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/transitive')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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_island
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_island')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_object_gap')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_questions_subject_gap_long_distance')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_no_gap_long_distance')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
מה_מול_זה_עם_פער
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}
מה_מול_זה_עם_פער_למרחק_ארוך
השתמש בפקודה הבאה כדי לטעון מערך נתונים זה ב-TFDS:
ds = tfds.load('huggingface:blimp/wh_vs_that_with_gap_long_distance')
- תיאור :
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.
- רישיון : אין רישיון ידוע
- גרסה : 0.1.0
- פיצולים :
| לְפַצֵל | דוגמאות |
|---|---|
'train' | 1000 |
- מאפיינים :
{
"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"
}
}