{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:7NI2IJ6RIRBPXALICNUIYNUYEP","short_pith_number":"pith:7NI2IJ6R","schema_version":"1.0","canonical_sha256":"fb51a427d14442fb816813688c369823c1349f5d4221e245dde70226114d1cd4","source":{"kind":"arxiv","id":"2412.08434","version":2},"attestation_state":"computed","paper":{"title":"Mitigating Out-of-Entity Errors in Named Entity Recognition: A Sentence-Level Strategy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chengwei Hu, Deqing Yang, Guochao Jiang, Zepeng Ding, Ziqin Luo","submitted_at":"2024-12-11T14:55:48Z","abstract_excerpt":"Many previous models of named entity recognition (NER) suffer from the problem of Out-of-Entity (OOE), i.e., the tokens in the entity mentions of the test samples have not appeared in the training samples, which hinders the achievement of satisfactory performance. To improve OOE-NER performance, in this paper, we propose a new framework, namely S+NER, which fully leverages sentence-level information. Our S+NER achieves better OOE-NER performance mainly due to the following two particular designs. 1) It first exploits the pre-trained language model's capability of understanding the target entit"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2412.08434","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-12-11T14:55:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"97bb5e2f17154f7059d38df6b5bae3e2b4d0a39e6b9ed118275e11393b9031b8","abstract_canon_sha256":"159e33e08d6877f88e84f3caa5a668058ed0f9d45bd1169c10d147f9d5181712"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:59:56.922151Z","signature_b64":"O0wpGG7JA4NboNsumGxAU3i8G5GNNGUzsPsemzIOH6QgUAMxNBIRP+9BOV0+qNBeV1P0Ownft7tcV7+jtFUZDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb51a427d14442fb816813688c369823c1349f5d4221e245dde70226114d1cd4","last_reissued_at":"2026-07-05T09:59:56.921789Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:59:56.921789Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Mitigating Out-of-Entity Errors in Named Entity Recognition: A Sentence-Level Strategy","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chengwei Hu, Deqing Yang, Guochao Jiang, Zepeng Ding, Ziqin Luo","submitted_at":"2024-12-11T14:55:48Z","abstract_excerpt":"Many previous models of named entity recognition (NER) suffer from the problem of Out-of-Entity (OOE), i.e., the tokens in the entity mentions of the test samples have not appeared in the training samples, which hinders the achievement of satisfactory performance. To improve OOE-NER performance, in this paper, we propose a new framework, namely S+NER, which fully leverages sentence-level information. Our S+NER achieves better OOE-NER performance mainly due to the following two particular designs. 1) It first exploits the pre-trained language model's capability of understanding the target entit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.08434","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2412.08434/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2412.08434","created_at":"2026-07-05T09:59:56.921845+00:00"},{"alias_kind":"arxiv_version","alias_value":"2412.08434v2","created_at":"2026-07-05T09:59:56.921845+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.08434","created_at":"2026-07-05T09:59:56.921845+00:00"},{"alias_kind":"pith_short_12","alias_value":"7NI2IJ6RIRBP","created_at":"2026-07-05T09:59:56.921845+00:00"},{"alias_kind":"pith_short_16","alias_value":"7NI2IJ6RIRBPXALI","created_at":"2026-07-05T09:59:56.921845+00:00"},{"alias_kind":"pith_short_8","alias_value":"7NI2IJ6R","created_at":"2026-07-05T09:59:56.921845+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP","json":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP.json","graph_json":"https://pith.science/api/pith-number/7NI2IJ6RIRBPXALICNUIYNUYEP/graph.json","events_json":"https://pith.science/api/pith-number/7NI2IJ6RIRBPXALICNUIYNUYEP/events.json","paper":"https://pith.science/paper/7NI2IJ6R"},"agent_actions":{"view_html":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP","download_json":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP.json","view_paper":"https://pith.science/paper/7NI2IJ6R","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2412.08434&json=true","fetch_graph":"https://pith.science/api/pith-number/7NI2IJ6RIRBPXALICNUIYNUYEP/graph.json","fetch_events":"https://pith.science/api/pith-number/7NI2IJ6RIRBPXALICNUIYNUYEP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP/action/storage_attestation","attest_author":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP/action/author_attestation","sign_citation":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP/action/citation_signature","submit_replication":"https://pith.science/pith/7NI2IJ6RIRBPXALICNUIYNUYEP/action/replication_record"}},"created_at":"2026-07-05T09:59:56.921845+00:00","updated_at":"2026-07-05T09:59:56.921845+00:00"}