ไซเทล

อ้างอิง:

snli_format

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:scitail/snli_format')
  • คำอธิบาย :
The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question 
and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information 
retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We 
crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create 
the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples 
with neutral label
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชั่น : 1.1.0
  • แยก :
แยก ตัวอย่าง
'test' 2126
'train' 23596
'validation' 1304
  • คุณสมบัติ :
{
    "sentence1_binary_parse": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence1_parse": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2_parse": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "annotator_labels": {
        "feature": {
            "dtype": "string",
            "id": null,
            "_type": "Value"
        },
        "length": -1,
        "id": null,
        "_type": "Sequence"
    },
    "gold_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

tsv_format

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:scitail/tsv_format')
  • คำอธิบาย :
The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question 
and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information 
retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We 
crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create 
the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples 
with neutral label
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชั่น : 1.1.0
  • แยก :
แยก ตัวอย่าง
'test' 2126
'train' 23097
'validation' 1304
  • คุณสมบัติ :
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

dgem_format

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:scitail/dgem_format')
  • คำอธิบาย :
The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question 
and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information 
retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We 
crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create 
the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples 
with neutral label
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชั่น : 1.1.0
  • แยก :
แยก ตัวอย่าง
'test' 2126
'train' 23088
'validation' 1304
  • คุณสมบัติ :
{
    "premise": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "hypothesis_graph_structure": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ตัวทำนาย_รูปแบบ

ใช้คำสั่งต่อไปนี้เพื่อโหลดชุดข้อมูลนี้ใน TFDS:

ds = tfds.load('huggingface:scitail/predictor_format')
  • คำอธิบาย :
The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question 
and the correct answer choice are converted into an assertive statement to form the hypothesis. We use information 
retrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We 
crowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create 
the SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples 
with neutral label
  • ใบอนุญาต : ไม่มีใบอนุญาตที่รู้จัก
  • เวอร์ชั่น : 1.1.0
  • แยก :
แยก ตัวอย่าง
'test' 2126
'train' 23587
'validation' 1304
  • คุณสมบัติ :
{
    "answer": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2_structure": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence1": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "sentence2": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "gold_label": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "question": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}