albertvillanova HF staff commited on
Commit
29c8a87
1 Parent(s): 473d8d4

Add dgem_format data files

Browse files
README.md CHANGED
@@ -16,16 +16,16 @@ dataset_info:
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  dtype: string
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  splits:
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  - name: train
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- num_bytes: 6832104
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  num_examples: 23088
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  - name: test
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- num_bytes: 608213
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  num_examples: 2126
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  - name: validation
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- num_bytes: 394040
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  num_examples: 1304
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- download_size: 14174621
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- dataset_size: 7834357
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  - config_name: predictor_format
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  features:
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  - name: answer
@@ -101,6 +101,14 @@ dataset_info:
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  download_size: 1836546
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  dataset_size: 5277216
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  configs:
 
 
 
 
 
 
 
 
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  - config_name: snli_format
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  data_files:
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  - split: train
 
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  dtype: string
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  splits:
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  - name: train
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+ num_bytes: 6817626
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  num_examples: 23088
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  - name: test
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+ num_bytes: 606867
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  num_examples: 2126
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  - name: validation
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+ num_bytes: 393209
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  num_examples: 1304
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+ download_size: 2007018
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+ dataset_size: 7817702
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  - config_name: predictor_format
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  features:
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  - name: answer
 
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  download_size: 1836546
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  dataset_size: 5277216
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  configs:
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+ - config_name: dgem_format
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+ data_files:
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+ - split: train
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+ path: dgem_format/train-*
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+ - split: test
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+ path: dgem_format/test-*
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+ - split: validation
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+ path: dgem_format/validation-*
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  - config_name: snli_format
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  data_files:
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  - split: train
dataset_infos.json CHANGED
@@ -125,39 +125,34 @@
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  "size_in_bytes": 7113762
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  },
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  "dgem_format": {
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- "description": "The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question \nand the correct answer choice are converted into an assertive statement to form the hypothesis. We use information \nretrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We \ncrowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create \nthe SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples \nwith neutral label\n",
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  "citation": "inproceedings{scitail,\n Author = {Tushar Khot and Ashish Sabharwal and Peter Clark},\n Booktitle = {AAAI},\n Title = {{SciTail}: A Textual Entailment Dataset from Science Question Answering},\n Year = {2018}\n}\n",
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  "homepage": "https://allenai.org/data/scitail",
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  "license": "",
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  "features": {
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  "premise": {
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  "dtype": "string",
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- "id": null,
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  "_type": "Value"
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  "hypothesis": {
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  "dtype": "string",
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  "label": {
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  "hypothesis_graph_structure": {
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  "_type": "Value"
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  "builder_name": "scitail",
 
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  "config_name": "dgem_format",
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  "version": {
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  "version_str": "1.1.0",
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  "description": "",
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@@ -165,32 +160,26 @@
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- "dataset_name": "scitail"
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- "dataset_name": "scitail"
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  },
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  "validation": {
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  "name": "validation",
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  "num_examples": 1304,
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- "dataset_name": "scitail"
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- }
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- },
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- "size_in_bytes": 22008978
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  "predictor_format": {
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  "description": "The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question \nand the correct answer choice are converted into an assertive statement to form the hypothesis. We use information \nretrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We \ncrowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create \nthe SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples \nwith neutral label\n",
 
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  "size_in_bytes": 7113762
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  },
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  "dgem_format": {
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+ "description": "The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question\nand the correct answer choice are converted into an assertive statement to form the hypothesis. We use information\nretrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We\ncrowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create\nthe SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples\nwith neutral label\n",
129
  "citation": "inproceedings{scitail,\n Author = {Tushar Khot and Ashish Sabharwal and Peter Clark},\n Booktitle = {AAAI},\n Title = {{SciTail}: A Textual Entailment Dataset from Science Question Answering},\n Year = {2018}\n}\n",
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  "homepage": "https://allenai.org/data/scitail",
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  "license": "",
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  "_type": "Value"
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  "builder_name": "scitail",
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  "version_str": "1.1.0",
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  "description": "",
 
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  "predictor_format": {
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  "description": "The SciTail dataset is an entailment dataset created from multiple-choice science exams and web sentences. Each question \nand the correct answer choice are converted into an assertive statement to form the hypothesis. We use information \nretrieval to obtain relevant text from a large text corpus of web sentences, and use these sentences as a premise P. We \ncrowdsource the annotation of such premise-hypothesis pair as supports (entails) or not (neutral), in order to create \nthe SciTail dataset. The dataset contains 27,026 examples with 10,101 examples with entails label and 16,925 examples \nwith neutral label\n",
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