{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:BPL22URQ4U62KXOOPLBBDNJXA4","short_pith_number":"pith:BPL22URQ","schema_version":"1.0","canonical_sha256":"0bd7ad5230e53da55dce7ac211b537071a505e581c159553da91d78f0e0103fd","source":{"kind":"arxiv","id":"2010.14123","version":1},"attestation_state":"computed","paper":{"title":"Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Thien Huu Nguyen, Tuan Ngo Nguyen, Viet Dac Lai","submitted_at":"2020-10-27T08:28:28Z","abstract_excerpt":"Recent studies on event detection (ED) haveshown that the syntactic dependency graph canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per-formance. However, the computation of thehidden vectors in such graph-based models isagnostic to the trigger candidate words, po-tentially leaving irrelevant information for thetrigger candidate for event prediction. In addi-tion, the current models for ED fail to exploitthe overall contextual importance scores of thewords, which can be obtained via the depen-dency tree, to boost the performance. In thisstudy, we propose"},"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":"2010.14123","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2020-10-27T08:28:28Z","cross_cats_sorted":[],"title_canon_sha256":"275ed9cf7e39ae22d568192786f1559b35cefd5b7916c6faccfae9f89bd5dcba","abstract_canon_sha256":"6431c0b925cc20651c1273ee6961bc27988b68b3bab1e786a22d1b51015e644b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:46:31.667581Z","signature_b64":"f94BXSmC5jroAb9HrjMnBbVFD8iGNC5c0GEHxNDoE6aH/tFO8OlK8FJ2AFoYgEhzUaZPxHI8ZnwzANDVj/GwDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0bd7ad5230e53da55dce7ac211b537071a505e581c159553da91d78f0e0103fd","last_reissued_at":"2026-07-05T01:46:31.667176Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:46:31.667176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Thien Huu Nguyen, Tuan Ngo Nguyen, Viet Dac Lai","submitted_at":"2020-10-27T08:28:28Z","abstract_excerpt":"Recent studies on event detection (ED) haveshown that the syntactic dependency graph canbe employed in graph convolution neural net-works (GCN) to achieve state-of-the-art per-formance. However, the computation of thehidden vectors in such graph-based models isagnostic to the trigger candidate words, po-tentially leaving irrelevant information for thetrigger candidate for event prediction. In addi-tion, the current models for ED fail to exploitthe overall contextual importance scores of thewords, which can be obtained via the depen-dency tree, to boost the performance. In thisstudy, we propose"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.14123","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/2010.14123/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":"2010.14123","created_at":"2026-07-05T01:46:31.667243+00:00"},{"alias_kind":"arxiv_version","alias_value":"2010.14123v1","created_at":"2026-07-05T01:46:31.667243+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.14123","created_at":"2026-07-05T01:46:31.667243+00:00"},{"alias_kind":"pith_short_12","alias_value":"BPL22URQ4U62","created_at":"2026-07-05T01:46:31.667243+00:00"},{"alias_kind":"pith_short_16","alias_value":"BPL22URQ4U62KXOO","created_at":"2026-07-05T01:46:31.667243+00:00"},{"alias_kind":"pith_short_8","alias_value":"BPL22URQ","created_at":"2026-07-05T01:46:31.667243+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/BPL22URQ4U62KXOOPLBBDNJXA4","json":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4.json","graph_json":"https://pith.science/api/pith-number/BPL22URQ4U62KXOOPLBBDNJXA4/graph.json","events_json":"https://pith.science/api/pith-number/BPL22URQ4U62KXOOPLBBDNJXA4/events.json","paper":"https://pith.science/paper/BPL22URQ"},"agent_actions":{"view_html":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4","download_json":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4.json","view_paper":"https://pith.science/paper/BPL22URQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2010.14123&json=true","fetch_graph":"https://pith.science/api/pith-number/BPL22URQ4U62KXOOPLBBDNJXA4/graph.json","fetch_events":"https://pith.science/api/pith-number/BPL22URQ4U62KXOOPLBBDNJXA4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4/action/storage_attestation","attest_author":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4/action/author_attestation","sign_citation":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4/action/citation_signature","submit_replication":"https://pith.science/pith/BPL22URQ4U62KXOOPLBBDNJXA4/action/replication_record"}},"created_at":"2026-07-05T01:46:31.667243+00:00","updated_at":"2026-07-05T01:46:31.667243+00:00"}