Datasets:

community-datasets
/

generics_kb

- {"generics_kb_best": {"description": "The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as \"Dogs bark,\" and \"Trees remove carbon dioxide from the atmosphere.\" Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle = {GenericsKB: A Knowledge Base of Generic Statements},\nauthors={Sumithra Bhakthavatsalam, Chloe Anastasiades, Peter Clark},\nyear={2020},\npublisher = {Allen Institute for AI},\n}\n", "homepage": "https://allenai.org/data/genericskb", "license": "cc-by-4.0", "features": {"source": {"dtype": "string", "id": null, "_type": "Value"}, "term": {"dtype": "string", "id": null, "_type": "Value"}, "quantifier_frequency": {"dtype": "string", "id": null, "_type": "Value"}, "quantifier_number": {"dtype": "string", "id": null, "_type": "Value"}, "generic_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "score": {"dtype": "float64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "generics_kb", "config_name": "generics_kb_best", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 99897719, "num_examples": 1020868, "dataset_name": "generics_kb"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=12DfIzoWyHIQqssgUgDvz3VG8_ScSh6ng&export=download": {"num_bytes": 94850525, "checksum": "0668b23c8b1579b6a76fcf48e04f3c9ea039ca9048a26848151d689deabb75e2"}}, "download_size": 94850525, "post_processing_size": null, "dataset_size": 99897719, "size_in_bytes": 194748244}, "generics_kb": {"description": "The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as \"Dogs bark,\" and \"Trees remove carbon dioxide from the atmosphere.\" Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle = {GenericsKB: A Knowledge Base of Generic Statements},\nauthors={Sumithra Bhakthavatsalam, Chloe Anastasiades, Peter Clark},\nyear={2020},\npublisher = {Allen Institute for AI},\n}\n", "homepage": "https://allenai.org/data/genericskb", "license": "cc-by-4.0", "features": {"source": {"dtype": "string", "id": null, "_type": "Value"}, "term": {"dtype": "string", "id": null, "_type": "Value"}, "quantifier_frequency": {"dtype": "string", "id": null, "_type": "Value"}, "quantifier_number": {"dtype": "string", "id": null, "_type": "Value"}, "generic_sentence": {"dtype": "string", "id": null, "_type": "Value"}, "score": {"dtype": "float64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "generics_kb", "config_name": "generics_kb", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 348158966, "num_examples": 3433000, "dataset_name": "generics_kb"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=1UOIEzQTid7SzKx2tbwSSPxl7g-CjpoZa&export=download": {"num_bytes": 343284785, "checksum": "7ec2419e700b3425129032f75f0bb01887bdb84231526468751d6cc2a9b9e61e"}}, "download_size": 343284785, "post_processing_size": null, "dataset_size": 348158966, "size_in_bytes": 691443751}, "generics_kb_simplewiki": {"description": "The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as \"Dogs bark,\" and \"Trees remove carbon dioxide from the atmosphere.\" Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle = {GenericsKB: A Knowledge Base of Generic Statements},\nauthors={Sumithra Bhakthavatsalam, Chloe Anastasiades, Peter Clark},\nyear={2020},\npublisher = {Allen Institute for AI},\n}\n", "homepage": "https://allenai.org/data/genericskb", "license": "cc-by-4.0", "features": {"source_name": {"dtype": "string", "id": null, "_type": "Value"}, "sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentences_before": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "sentences_after": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "concept_name": {"dtype": "string", "id": null, "_type": "Value"}, "quantifiers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "id": {"dtype": "string", "id": null, "_type": "Value"}, "bert_score": {"dtype": "float64", "id": null, "_type": "Value"}, "headings": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "categories": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "generics_kb", "config_name": "generics_kb_simplewiki", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 10039355, "num_examples": 12765, "dataset_name": "generics_kb"}}, "download_checksums": {"https://drive.google.com/u/0/uc?id=1SpN9Qc7XRy5xs4tIfXkcLOEAP2IVaK15&export=download": {"num_bytes": 16437369, "checksum": "f6c0da9c9100172e8979907448497717d8ea1a50ee96aa2b81e447423c6cd0bb"}}, "download_size": 16437369, "post_processing_size": null, "dataset_size": 10039355, "size_in_bytes": 26476724}, "generics_kb_waterloo": {"description": "The GenericsKB contains 3.4M+ generic sentences about the world, i.e., sentences expressing general truths such as \"Dogs bark,\" and \"Trees remove carbon dioxide from the atmosphere.\" Generics are potentially useful as a knowledge source for AI systems requiring general world knowledge. The GenericsKB is the first large-scale resource containing naturally occurring generic sentences (as opposed to extracted or crowdsourced triples), and is rich in high-quality, general, semantically complete statements. Generics were primarily extracted from three large text sources, namely the Waterloo Corpus, selected parts of Simple Wikipedia, and the ARC Corpus. A filtered, high-quality subset is also available in GenericsKB-Best, containing 1,020,868 sentences. We recommend you start with GenericsKB-Best.\n", "citation": "@InProceedings{huggingface:dataset,\ntitle = {GenericsKB: A Knowledge Base of Generic Statements},\nauthors={Sumithra Bhakthavatsalam, Chloe Anastasiades, Peter Clark},\nyear={2020},\npublisher = {Allen Institute for AI},\n}\n", "homepage": "https://allenai.org/data/genericskb", "license": "cc-by-4.0", "features": {"source_name": {"dtype": "string", "id": null, "_type": "Value"}, "sentence": {"dtype": "string", "id": null, "_type": "Value"}, "sentences_before": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "sentences_after": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "concept_name": {"dtype": "string", "id": null, "_type": "Value"}, "quantifiers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "id": {"dtype": "string", "id": null, "_type": "Value"}, "bert_score": {"dtype": "float64", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "generics_kb", "config_name": "generics_kb_waterloo", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 4277214701, "num_examples": 3666725, "dataset_name": "generics_kb"}}, "download_checksums": {}, "download_size": 0, "post_processing_size": null, "dataset_size": 4277214701, "size_in_bytes": 4277214701}}