{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:55VALLB7TWSTUMSY4SXJWJ2OG6","short_pith_number":"pith:55VALLB7","schema_version":"1.0","canonical_sha256":"ef6a05ac3f9da53a3258e4ae9b274e37beadbd0d0e2c73e84fc41506f10dcff7","source":{"kind":"arxiv","id":"1804.05918","version":1},"attestation_state":"computed","paper":{"title":"Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ruihong Huang, Zeyu Dai","submitted_at":"2018-04-16T20:01:06Z","abstract_excerpt":"We argue that semantic meanings of a sentence or clause can not be interpreted independently from the rest of a paragraph, or independently from all discourse relations and the overall paragraph-level discourse structure. With the goal of improving implicit discourse relation classification, we introduce a paragraph-level neural networks that model inter-dependencies between discourse units as well as discourse relation continuity and patterns, and predict a sequence of discourse relations in a paragraph. Experimental results show that our model outperforms the previous state-of-the-art system"},"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":"1804.05918","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-16T20:01:06Z","cross_cats_sorted":[],"title_canon_sha256":"fc762d8350b830896386964da9e3c49b310c200a5d3e9d26857a8b354ffcc507","abstract_canon_sha256":"201661344202642791a014341917c8e9edbc83acb456b7ff9016e114412d0ae5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:18:22.386081Z","signature_b64":"ERkKpy9JivfdB8G7o9c5rR0kYiJdM/EmvplXq05KeA45A7cw+tZNqC/0kVe2U6Gp38S2QZ1Ph/tcHK+Ve9dPDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef6a05ac3f9da53a3258e4ae9b274e37beadbd0d0e2c73e84fc41506f10dcff7","last_reissued_at":"2026-05-18T00:18:22.385385Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:18:22.385385Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Improving Implicit Discourse Relation Classification by Modeling Inter-dependencies of Discourse Units in a Paragraph","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ruihong Huang, Zeyu Dai","submitted_at":"2018-04-16T20:01:06Z","abstract_excerpt":"We argue that semantic meanings of a sentence or clause can not be interpreted independently from the rest of a paragraph, or independently from all discourse relations and the overall paragraph-level discourse structure. With the goal of improving implicit discourse relation classification, we introduce a paragraph-level neural networks that model inter-dependencies between discourse units as well as discourse relation continuity and patterns, and predict a sequence of discourse relations in a paragraph. Experimental results show that our model outperforms the previous state-of-the-art system"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.05918","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":""},"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":"1804.05918","created_at":"2026-05-18T00:18:22.385493+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.05918v1","created_at":"2026-05-18T00:18:22.385493+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.05918","created_at":"2026-05-18T00:18:22.385493+00:00"},{"alias_kind":"pith_short_12","alias_value":"55VALLB7TWST","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_16","alias_value":"55VALLB7TWSTUMSY","created_at":"2026-05-18T12:32:05.422762+00:00"},{"alias_kind":"pith_short_8","alias_value":"55VALLB7","created_at":"2026-05-18T12:32:05.422762+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/55VALLB7TWSTUMSY4SXJWJ2OG6","json":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6.json","graph_json":"https://pith.science/api/pith-number/55VALLB7TWSTUMSY4SXJWJ2OG6/graph.json","events_json":"https://pith.science/api/pith-number/55VALLB7TWSTUMSY4SXJWJ2OG6/events.json","paper":"https://pith.science/paper/55VALLB7"},"agent_actions":{"view_html":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6","download_json":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6.json","view_paper":"https://pith.science/paper/55VALLB7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.05918&json=true","fetch_graph":"https://pith.science/api/pith-number/55VALLB7TWSTUMSY4SXJWJ2OG6/graph.json","fetch_events":"https://pith.science/api/pith-number/55VALLB7TWSTUMSY4SXJWJ2OG6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6/action/storage_attestation","attest_author":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6/action/author_attestation","sign_citation":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6/action/citation_signature","submit_replication":"https://pith.science/pith/55VALLB7TWSTUMSY4SXJWJ2OG6/action/replication_record"}},"created_at":"2026-05-18T00:18:22.385493+00:00","updated_at":"2026-05-18T00:18:22.385493+00:00"}