{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:U25QTET67HADKMEP2M4AGSVQBS","short_pith_number":"pith:U25QTET6","schema_version":"1.0","canonical_sha256":"a6bb09927ef9c035308fd338034ab00c8e0dfd35d9bc58b4e1afa62282c06298","source":{"kind":"arxiv","id":"2210.03949","version":1},"attestation_state":"computed","paper":{"title":"ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bin Xu, Jifan Yu, Jinxin Liu, Ji Qi, Juanzi Li, Kaisheng Zeng, Lei Hou, Qi Gao","submitted_at":"2022-10-08T07:36:04Z","abstract_excerpt":"Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available during training, which causes that most methods adopt heuristic or syntactic rules to construct a prior graph as a pseudo proxy. In this paper, we propose $\\textbf{ConstGCN}$, a novel graph convolutional network which performs knowledge-based information propagation between entities along with all specific relation spaces without any prior graph construction. Specifically, it updates the entity representation by aggr"},"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":"2210.03949","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-10-08T07:36:04Z","cross_cats_sorted":[],"title_canon_sha256":"bb610bddb0ade9c9b99e732bdea58f36f210b36719781324bbe8916250624b9c","abstract_canon_sha256":"301d366d012d33f1e8c0bfafa4b971097379877d378e745c91f9ccd4fc845347"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:04:34.270828Z","signature_b64":"m6UK7D9NCORw2c+WACMeP8TNByboBqtcKZthuKlpSf59xFpPvyIFs/ZtJhctX1vu3Zx+BAYmxQ+i/5aPeFriBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6bb09927ef9c035308fd338034ab00c8e0dfd35d9bc58b4e1afa62282c06298","last_reissued_at":"2026-07-05T05:04:34.270385Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:04:34.270385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bin Xu, Jifan Yu, Jinxin Liu, Ji Qi, Juanzi Li, Kaisheng Zeng, Lei Hou, Qi Gao","submitted_at":"2022-10-08T07:36:04Z","abstract_excerpt":"Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available during training, which causes that most methods adopt heuristic or syntactic rules to construct a prior graph as a pseudo proxy. In this paper, we propose $\\textbf{ConstGCN}$, a novel graph convolutional network which performs knowledge-based information propagation between entities along with all specific relation spaces without any prior graph construction. Specifically, it updates the entity representation by aggr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.03949","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/2210.03949/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":"2210.03949","created_at":"2026-07-05T05:04:34.270444+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.03949v1","created_at":"2026-07-05T05:04:34.270444+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.03949","created_at":"2026-07-05T05:04:34.270444+00:00"},{"alias_kind":"pith_short_12","alias_value":"U25QTET67HAD","created_at":"2026-07-05T05:04:34.270444+00:00"},{"alias_kind":"pith_short_16","alias_value":"U25QTET67HADKMEP","created_at":"2026-07-05T05:04:34.270444+00:00"},{"alias_kind":"pith_short_8","alias_value":"U25QTET6","created_at":"2026-07-05T05:04:34.270444+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/U25QTET67HADKMEP2M4AGSVQBS","json":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS.json","graph_json":"https://pith.science/api/pith-number/U25QTET67HADKMEP2M4AGSVQBS/graph.json","events_json":"https://pith.science/api/pith-number/U25QTET67HADKMEP2M4AGSVQBS/events.json","paper":"https://pith.science/paper/U25QTET6"},"agent_actions":{"view_html":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS","download_json":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS.json","view_paper":"https://pith.science/paper/U25QTET6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.03949&json=true","fetch_graph":"https://pith.science/api/pith-number/U25QTET67HADKMEP2M4AGSVQBS/graph.json","fetch_events":"https://pith.science/api/pith-number/U25QTET67HADKMEP2M4AGSVQBS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS/action/storage_attestation","attest_author":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS/action/author_attestation","sign_citation":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS/action/citation_signature","submit_replication":"https://pith.science/pith/U25QTET67HADKMEP2M4AGSVQBS/action/replication_record"}},"created_at":"2026-07-05T05:04:34.270444+00:00","updated_at":"2026-07-05T05:04:34.270444+00:00"}