Riferimenti:
snli_format
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:scitail/snli_format')
- Descrizione :
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
- Licenza : nessuna licenza conosciuta
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2126 |
'train' | 23596 |
'validation' | 1304 |
- Caratteristiche :
{
"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"
}
}
formato_tsv
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:scitail/tsv_format')
- Descrizione :
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
- Licenza : nessuna licenza conosciuta
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2126 |
'train' | 23097 |
'validation' | 1304 |
- Caratteristiche :
{
"premise": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"hypothesis": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"label": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
dgem_format
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:scitail/dgem_format')
- Descrizione :
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
- Licenza : nessuna licenza conosciuta
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2126 |
'train' | 23088 |
'validation' | 1304 |
- Caratteristiche :
{
"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"
}
}
predittore_format
Utilizzare il comando seguente per caricare questo set di dati in TFDS:
ds = tfds.load('huggingface:scitail/predictor_format')
- Descrizione :
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
- Licenza : nessuna licenza conosciuta
- Versione : 1.1.0
- Divide :
| Diviso | Esempi |
|---|---|
'test' | 2126 |
'train' | 23587 |
'validation' | 1304 |
- Caratteristiche :
{
"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"
}
}