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- {"PiC--phrase_similarity": {"description": "Phrase in Context is a curated benchmark for phrase understanding and semantic search, consisting of three tasks of increasing difficulty: Phrase Similarity (PS), Phrase Retrieval (PR) and Phrase Sense Disambiguation (PSD). The datasets are annotated by 13 linguistic experts on Upwork and verified by two groups: ~1000 AMT crowdworkers and another set of 5 linguistic experts. PiC benchmark is distributed under CC-BY-NC 4.0.\n", "citation": "@article{pham2022PiC,\n title={PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search},\n author={Pham, Thang M and Yoon, Seunghyun and Bui, Trung and Nguyen, Anh},\n journal={arXiv preprint arXiv:2207.09068},\n year={2022}\n}\n", "homepage": "https://phrase-in-context.github.io/", "license": "CC-BY-NC-4.0", "features": {"phrase1": {"dtype": "string", "id": null, "_type": "Value"}, "phrase2": {"dtype": "string", "id": null, "_type": "Value"}, "sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["negative", "positive"], "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "phrase_similarity", "config_name": "PS-hard", "version": {"version_str": "1.0.4", "description": null, "major": 1, "minor": 0, "patch": 4}, "splits": {"train": {"name": "train", "num_bytes": 2174103, "num_examples": 7362, "dataset_name": "phrase_similarity"}, "validation": {"name": "validation", "num_bytes": 308376, "num_examples": 1052, "dataset_name": "phrase_similarity"}, "test": {"name": "test", "num_bytes": 625270, "num_examples": 2102, "dataset_name": "phrase_similarity"}}, "download_checksums": null, "download_size": 0, "post_processing_size": null, "dataset_size": 3107749, "size_in_bytes": 3107749}}
 
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+ {"PiC--phrase_similarity": {"description": "Phrase in Context is a curated benchmark for phrase understanding and semantic search, consisting of three tasks of increasing difficulty: Phrase Similarity (PS), Phrase Retrieval (PR) and Phrase Sense Disambiguation (PSD). The datasets are annotated by 13 linguistic experts on Upwork and verified by two groups: ~1000 AMT crowdworkers and another set of 5 linguistic experts. PiC benchmark is distributed under CC-BY-NC 4.0.\n", "citation": "@article{pham2022PiC,\n title={PiC: A Phrase-in-Context Dataset for Phrase Understanding and Semantic Search},\n author={Pham, Thang M and Yoon, Seunghyun and Bui, Trung and Nguyen, Anh},\n journal={arXiv preprint arXiv:2207.09068},\n year={2022}\n}\n", "homepage": "https://phrase-in-context.github.io/", "license": "CC-BY-NC-4.0", "features": {"phrase1": {"dtype": "string", "id": null, "_type": "Value"}, "phrase2": {"dtype": "string", "id": null, "_type": "Value"}, "sentence1": {"dtype": "string", "id": null, "_type": "Value"}, "sentence2": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 2, "names": ["negative", "positive"], "id": null, "_type": "ClassLabel"}, "idx": {"dtype": "int32", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "phrase_similarity", "config_name": "PS-hard", "version": {"version_str": "1.0.5", "description": null, "major": 1, "minor": 0, "patch": 5}, "splits": {"train": {"name": "train", "num_bytes": 2113667, "num_examples": 7146, "dataset_name": "phrase_similarity"}, "validation": {"name": "validation", "num_bytes": 301731, "num_examples": 1022, "dataset_name": "phrase_similarity"}, "test": {"name": "test", "num_bytes": 605474, "num_examples": 2040, "dataset_name": "phrase_similarity"}}, "download_checksums": null, "download_size": 1758005, "post_processing_size": null, "dataset_size": 3020872, "size_in_bytes": 4778877}}