Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Source Datasets:
original
ArXiv:
License:
davzoku commited on
Commit
190ec4b
1 Parent(s): 4c40e64

Convert dataset to Parquet

Browse files
README.md CHANGED
@@ -72,17 +72,26 @@ dataset_info:
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  - name: id
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  dtype: string
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  splits:
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- - name: test
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- num_bytes: 870809
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  - name: train
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  num_examples: 8194
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  - name: validation
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  num_examples: 916
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- download_size: 23189911
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- dataset_size: 5145009
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  # Dataset Card for "scicite"
 
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  - name: id
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  dtype: string
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  splits:
 
 
 
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  - name: train
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+ num_bytes: 3828509
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  num_examples: 8194
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  - name: validation
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+ num_bytes: 428551
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  num_examples: 916
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+ - name: test
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+ num_bytes: 867294
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+ num_examples: 1859
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+ download_size: 3561554
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+ dataset_size: 5124354
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: validation
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+ path: data/validation-*
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+ - split: test
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+ path: data/test-*
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  ---
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  # Dataset Card for "scicite"
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data/validation-00000-of-00001.parquet ADDED
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dataset_infos.json CHANGED
@@ -1 +1,115 @@
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- {"default": {"description": "\nThis is a dataset for classifying citation intents in academic papers.\nThe main citation intent label for each Json object is specified with the label\nkey while the citation context is specified in with a context key. Example:\n{\n 'string': 'In chacma baboons, male-infant relationships can be linked to both\n formation of friendships and paternity success [30,31].'\n 'sectionName': 'Introduction',\n 'label': 'background',\n 'citingPaperId': '7a6b2d4b405439',\n 'citedPaperId': '9d1abadc55b5e0',\n ...\n }\nYou may obtain the full information about the paper using the provided paper ids\nwith the Semantic Scholar API (https://api.semanticscholar.org/).\nThe labels are:\nMethod, Background, Result\n", "citation": "\n@InProceedings{Cohan2019Structural,\n author={Arman Cohan and Waleed Ammar and Madeleine Van Zuylen and Field Cady},\n title={Structural Scaffolds for Citation Intent Classification in Scientific Publications},\n booktitle=\"NAACL\",\n year=\"2019\"\n}\n", "homepage": "https://github.com/allenai/scicite", "license": "", "features": {"string": {"dtype": "string", "id": null, "_type": "Value"}, "sectionName": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["method", "background", "result"], "names_file": null, "id": null, "_type": "ClassLabel"}, "citingPaperId": {"dtype": "string", "id": null, "_type": "Value"}, "citedPaperId": {"dtype": "string", "id": null, "_type": "Value"}, "excerpt_index": {"dtype": "int32", "id": null, "_type": "Value"}, "isKeyCitation": {"dtype": "bool", "id": null, "_type": "Value"}, "label2": {"num_classes": 4, "names": ["supportive", "not_supportive", "cant_determine", "none"], "names_file": null, "id": null, "_type": "ClassLabel"}, "citeEnd": {"dtype": "int64", "id": null, "_type": "Value"}, "citeStart": {"dtype": "int64", "id": null, "_type": "Value"}, "source": {"num_classes": 7, "names": ["properNoun", "andPhrase", "acronym", "etAlPhrase", "explicit", "acronymParen", "nan"], "names_file": null, "id": null, "_type": "ClassLabel"}, "label_confidence": {"dtype": "float32", "id": null, "_type": "Value"}, "label2_confidence": {"dtype": "float32", "id": null, "_type": "Value"}, "id": {"dtype": "string", "id": null, "_type": "Value"}}, "supervised_keys": null, "builder_name": "scicite", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "datasets_version_to_prepare": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 870809, "num_examples": 1859, "dataset_name": "scicite"}, "train": {"name": "train", "num_bytes": 3843904, "num_examples": 8194, "dataset_name": "scicite"}, "validation": {"name": "validation", "num_bytes": 430296, "num_examples": 916, "dataset_name": "scicite"}}, "download_checksums": {"https://s3-us-west-2.amazonaws.com/ai2-s2-research/scicite/scicite.tar.gz": {"num_bytes": 23189911, "checksum": "711ece2c4e61d116c8ae5bb07e9fbb2ee9ff7bba004b4cab7fbd0ac3af499193"}}, "download_size": 23189911, "dataset_size": 5145009, "size_in_bytes": 28334920}}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "default": {
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+ "description": "\nThis is a dataset for classifying citation intents in academic papers.\nThe main citation intent label for each Json object is specified with the label\nkey while the citation context is specified in with a context key. Example:\n{\n 'string': 'In chacma baboons, male-infant relationships can be linked to both\n formation of friendships and paternity success [30,31].'\n 'sectionName': 'Introduction',\n 'label': 'background',\n 'citingPaperId': '7a6b2d4b405439',\n 'citedPaperId': '9d1abadc55b5e0',\n ...\n }\nYou may obtain the full information about the paper using the provided paper ids\nwith the Semantic Scholar API (https://api.semanticscholar.org/).\nThe labels are:\nMethod, Background, Result\n",
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+ "citation": "\n@InProceedings{Cohan2019Structural,\n author={Arman Cohan and Waleed Ammar and Madeleine Van Zuylen and Field Cady},\n title={Structural Scaffolds for Citation Intent Classification in Scientific Publications},\n booktitle={NAACL},\n year={2019}\n}\n",
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+ }