{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:WYA726KZJ7INPNA35E6D2THLEB","short_pith_number":"pith:WYA726KZ","schema_version":"1.0","canonical_sha256":"b601fd79594fd0d7b41be93c3d4ceb206fe93885e5f9e0fafb80cc56c149a46f","source":{"kind":"arxiv","id":"2211.00684","version":1},"attestation_state":"computed","paper":{"title":"TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chong Teng, Dongdong Xie, Donghong Ji, Fei Li, Jiang Liu, Jingye Li, Liang Zhao","submitted_at":"2022-11-01T18:17:49Z","abstract_excerpt":"So far, discontinuous named entity recognition (NER) has received increasing research attention and many related methods have surged such as hypergraph-based methods, span-based methods, and sequence-to-sequence (Seq2Seq) methods, etc. However, these methods more or less suffer from some problems such as decoding ambiguity and efficiency, which limit their performance. Recently, grid-tagging methods, which benefit from the flexible design of tagging systems and model architectures, have shown superiority to adapt for various information extraction tasks. In this paper, we follow the line of su"},"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":"2211.00684","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-11-01T18:17:49Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8cdde2f30cb2c729d30c73e6ce4bf4963b3316ad39ac813650eb7ed76a665440","abstract_canon_sha256":"0aff79492eb381083ce1e258c0a35f88e6a5fc62e349afaff04bd0131541d43e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:12:33.066124Z","signature_b64":"lrz2TEyy6E8G/dWHpuv+rEC+giimZ/ywxb9xeTpoJDoxt3IF5JVb6Xutxu3F+0HTBZ+vCEsetR/LKrpgpu1IAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b601fd79594fd0d7b41be93c3d4ceb206fe93885e5f9e0fafb80cc56c149a46f","last_reissued_at":"2026-07-05T05:12:33.065646Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:12:33.065646Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TOE: A Grid-Tagging Discontinuous NER Model Enhanced by Embedding Tag/Word Relations and More Fine-Grained Tags","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Chong Teng, Dongdong Xie, Donghong Ji, Fei Li, Jiang Liu, Jingye Li, Liang Zhao","submitted_at":"2022-11-01T18:17:49Z","abstract_excerpt":"So far, discontinuous named entity recognition (NER) has received increasing research attention and many related methods have surged such as hypergraph-based methods, span-based methods, and sequence-to-sequence (Seq2Seq) methods, etc. However, these methods more or less suffer from some problems such as decoding ambiguity and efficiency, which limit their performance. Recently, grid-tagging methods, which benefit from the flexible design of tagging systems and model architectures, have shown superiority to adapt for various information extraction tasks. In this paper, we follow the line of su"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.00684","kind":"arxiv","version":1},"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/2211.00684/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":"2211.00684","created_at":"2026-07-05T05:12:33.065708+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.00684v1","created_at":"2026-07-05T05:12:33.065708+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.00684","created_at":"2026-07-05T05:12:33.065708+00:00"},{"alias_kind":"pith_short_12","alias_value":"WYA726KZJ7IN","created_at":"2026-07-05T05:12:33.065708+00:00"},{"alias_kind":"pith_short_16","alias_value":"WYA726KZJ7INPNA3","created_at":"2026-07-05T05:12:33.065708+00:00"},{"alias_kind":"pith_short_8","alias_value":"WYA726KZ","created_at":"2026-07-05T05:12:33.065708+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/WYA726KZJ7INPNA35E6D2THLEB","json":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB.json","graph_json":"https://pith.science/api/pith-number/WYA726KZJ7INPNA35E6D2THLEB/graph.json","events_json":"https://pith.science/api/pith-number/WYA726KZJ7INPNA35E6D2THLEB/events.json","paper":"https://pith.science/paper/WYA726KZ"},"agent_actions":{"view_html":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB","download_json":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB.json","view_paper":"https://pith.science/paper/WYA726KZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.00684&json=true","fetch_graph":"https://pith.science/api/pith-number/WYA726KZJ7INPNA35E6D2THLEB/graph.json","fetch_events":"https://pith.science/api/pith-number/WYA726KZJ7INPNA35E6D2THLEB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB/action/storage_attestation","attest_author":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB/action/author_attestation","sign_citation":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB/action/citation_signature","submit_replication":"https://pith.science/pith/WYA726KZJ7INPNA35E6D2THLEB/action/replication_record"}},"created_at":"2026-07-05T05:12:33.065708+00:00","updated_at":"2026-07-05T05:12:33.065708+00:00"}