{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:CXPYLOEE644DCTSK47TAKCJUBO","short_pith_number":"pith:CXPYLOEE","schema_version":"1.0","canonical_sha256":"15df85b884f738314e4ae7e60509340b82a3696c99e3e63d3324eb415240f356","source":{"kind":"arxiv","id":"2505.18703","version":1},"attestation_state":"computed","paper":{"title":"Towards Semantic Integration of Opinions: Unified Opinion Concepts Ontology and Extraction Task","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dhairya Dalal, Gaurav Negi, Omnia Zayed, Paul Buitelaar","submitted_at":"2025-05-24T13:52:24Z","abstract_excerpt":"This paper introduces the Unified Opinion Concepts (UOC) ontology to integrate opinions within their semantic context. The UOC ontology bridges the gap between the semantic representation of opinion across different formulations. It is a unified conceptualisation based on the facets of opinions studied extensively in NLP and semantic structures described through symbolic descriptions. We further propose the Unified Opinion Concept Extraction (UOCE) task of extracting opinions from the text with enhanced expressivity. Additionally, we provide a manually extended and re-annotated evaluation data"},"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":"2505.18703","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-24T13:52:24Z","cross_cats_sorted":[],"title_canon_sha256":"601ff286ec0cc49b06032ac4be3237c2caaa3e7ae614745d49c98f3eb84297ca","abstract_canon_sha256":"28ca1bae1eeefe2c009a704efda1b93f52617972bc19cfbec3955f56331e4e8e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:18.147122Z","signature_b64":"VwEZR/Rq1lxR5yjGKGsp1rvFXIZEu209alB8JGVZ9/1b+9GKTtNzpy0fy1jmlKnECzBydE94ELRS88tbkUwjBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"15df85b884f738314e4ae7e60509340b82a3696c99e3e63d3324eb415240f356","last_reissued_at":"2026-07-05T11:09:18.146620Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:18.146620Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Semantic Integration of Opinions: Unified Opinion Concepts Ontology and Extraction Task","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dhairya Dalal, Gaurav Negi, Omnia Zayed, Paul Buitelaar","submitted_at":"2025-05-24T13:52:24Z","abstract_excerpt":"This paper introduces the Unified Opinion Concepts (UOC) ontology to integrate opinions within their semantic context. The UOC ontology bridges the gap between the semantic representation of opinion across different formulations. It is a unified conceptualisation based on the facets of opinions studied extensively in NLP and semantic structures described through symbolic descriptions. We further propose the Unified Opinion Concept Extraction (UOCE) task of extracting opinions from the text with enhanced expressivity. Additionally, we provide a manually extended and re-annotated evaluation data"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.18703","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/2505.18703/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":"2505.18703","created_at":"2026-07-05T11:09:18.146681+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.18703v1","created_at":"2026-07-05T11:09:18.146681+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.18703","created_at":"2026-07-05T11:09:18.146681+00:00"},{"alias_kind":"pith_short_12","alias_value":"CXPYLOEE644D","created_at":"2026-07-05T11:09:18.146681+00:00"},{"alias_kind":"pith_short_16","alias_value":"CXPYLOEE644DCTSK","created_at":"2026-07-05T11:09:18.146681+00:00"},{"alias_kind":"pith_short_8","alias_value":"CXPYLOEE","created_at":"2026-07-05T11:09:18.146681+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2509.02363","citing_title":"Towards Temporal Knowledge-Base Creation for Fine-Grained Opinion Analysis with Language Models","ref_index":37,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO","json":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO.json","graph_json":"https://pith.science/api/pith-number/CXPYLOEE644DCTSK47TAKCJUBO/graph.json","events_json":"https://pith.science/api/pith-number/CXPYLOEE644DCTSK47TAKCJUBO/events.json","paper":"https://pith.science/paper/CXPYLOEE"},"agent_actions":{"view_html":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO","download_json":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO.json","view_paper":"https://pith.science/paper/CXPYLOEE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.18703&json=true","fetch_graph":"https://pith.science/api/pith-number/CXPYLOEE644DCTSK47TAKCJUBO/graph.json","fetch_events":"https://pith.science/api/pith-number/CXPYLOEE644DCTSK47TAKCJUBO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO/action/storage_attestation","attest_author":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO/action/author_attestation","sign_citation":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO/action/citation_signature","submit_replication":"https://pith.science/pith/CXPYLOEE644DCTSK47TAKCJUBO/action/replication_record"}},"created_at":"2026-07-05T11:09:18.146681+00:00","updated_at":"2026-07-05T11:09:18.146681+00:00"}