Datasets:

INK-USC
/

numer_sense

- {"default": {"description": "NumerSense is a new numerical commonsense reasoning probing task, with a diagnostic dataset consisting of 3,145 masked-word-prediction probes.\n\nWe propose to study whether numerical commonsense knowledge can be induced from pre-trained language models like BERT, and to what extent this access to knowledge robust against adversarial examples is. We hope this will be beneficial for tasks such as knowledge base completion and open-domain question answering.\n", "citation": "@inproceedings{lin2020numersense,\n title={Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models},\n author={Bill Yuchen Lin and Seyeon Lee and Rahul Khanna and Xiang Ren}, \n booktitle={Proceedings of EMNLP},\n year={2020},\n note={to appear}\n}\n", "homepage": "https://inklab.usc.edu/NumerSense/", "license": "", "features": {"sentence": {"dtype": "string", "id": null, "_type": "Value"}, "target": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "builder_name": "numer_sense", "config_name": "default", "version": {"version_str": "0.0.0", "description": null, "major": 0, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 825865, "num_examples": 10444, "dataset_name": "numer_sense"}, "test_core": {"name": "test_core", "num_bytes": 62652, "num_examples": 1132, "dataset_name": "numer_sense"}, "test_all": {"name": "test_all", "num_bytes": 184180, "num_examples": 3146, "dataset_name": "numer_sense"}}, "download_checksums": {"https://raw.githubusercontent.com/INK-USC/NumerSense/main/data/train.masked.tsv": {"num_bytes": 763185, "checksum": "34cd706f4070907b8a9fa7200504bea099a6f34a343e282ae4f3a987ecd63d95"}, "https://raw.githubusercontent.com/INK-USC/NumerSense/main/data/test.core.masked.txt": {"num_bytes": 56983, "checksum": "ed8abedebf6875085619db2c1b966da63409a9b3d0ee3c8f1b1a6a6bcfe0d094"}, "https://raw.githubusercontent.com/INK-USC/NumerSense/main/data/test.all.masked.txt": {"num_bytes": 165295, "checksum": "eefc2649b8dd679d2722d41494b01821be5d76d45ba058c0bf71840fa353a89b"}}, "download_size": 985463, "post_processing_size": null, "dataset_size": 1072697, "size_in_bytes": 2058160}}