{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YOOMDMGNMYOX7GAU6JZEJIXVQG","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"b1e699833895c9aab7ff1e76a5a59274cfaee2649ba4ed0db603f160e39740c0","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-09-20T00:39:07Z","title_canon_sha256":"53d9040ef4ee866c95c8ee721341e2f5d8a4aeff048c5d27d622d3745f003109"},"schema_version":"1.0","source":{"id":"1909.09270","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1909.09270","created_at":"2026-07-05T00:05:56Z"},{"alias_kind":"arxiv_version","alias_value":"1909.09270v1","created_at":"2026-07-05T00:05:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.09270","created_at":"2026-07-05T00:05:56Z"},{"alias_kind":"pith_short_12","alias_value":"YOOMDMGNMYOX","created_at":"2026-07-05T00:05:56Z"},{"alias_kind":"pith_short_16","alias_value":"YOOMDMGNMYOX7GAU","created_at":"2026-07-05T00:05:56Z"},{"alias_kind":"pith_short_8","alias_value":"YOOMDMGN","created_at":"2026-07-05T00:05:56Z"}],"graph_snapshots":[{"event_id":"sha256:29994c66c890897b1f1c0e24709e5d516e535b055dcd034204692465d28af306","target":"graph","created_at":"2026-07-05T00:05:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/1909.09270/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Supervised machine learning assumes the availability of fully-labeled data, but in many cases, such as low-resource languages, the only data available is partially annotated. We study the problem of Named Entity Recognition (NER) with partially annotated training data in which a fraction of the named entities are labeled, and all other tokens, entities or otherwise, are labeled as non-entity by default. In order to train on this noisy dataset, we need to distinguish between the true and false negatives. To this end, we introduce a constraint-driven iterative algorithm that learns to detect fal","authors_text":"Chen-Tse Tsai, Dan Roth, Snigdha Chaturvedi, Stephen Mayhew","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-09-20T00:39:07Z","title":"Named Entity Recognition with Partially Annotated Training Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.09270","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8882f01e267990f2cfa684f5f64ef7bf22a267570630df6a488b80d692056ee3","target":"record","created_at":"2026-07-05T00:05:56Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"b1e699833895c9aab7ff1e76a5a59274cfaee2649ba4ed0db603f160e39740c0","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2019-09-20T00:39:07Z","title_canon_sha256":"53d9040ef4ee866c95c8ee721341e2f5d8a4aeff048c5d27d622d3745f003109"},"schema_version":"1.0","source":{"id":"1909.09270","kind":"arxiv","version":1}},"canonical_sha256":"c39cc1b0cd661d7f9814f27244a2f5819c95a0742e485bb415c9ab810714a9c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c39cc1b0cd661d7f9814f27244a2f5819c95a0742e485bb415c9ab810714a9c6","first_computed_at":"2026-07-05T00:05:56.980628Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:05:56.980628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vJN7YLwNRrw7n3d7sGENag4kvF1dkMJLji9qscosQCiGVOpiiO+QwGPg61yW9M7HXxITb+/sYcid18A7GeSrCw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:05:56.980975Z","signed_message":"canonical_sha256_bytes"},"source_id":"1909.09270","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8882f01e267990f2cfa684f5f64ef7bf22a267570630df6a488b80d692056ee3","sha256:29994c66c890897b1f1c0e24709e5d516e535b055dcd034204692465d28af306"],"state_sha256":"c363bc22076b0abd5ee3b708dc5a3c70cea52c738c31ca9a3c514726180a3d0f"}