{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2014:ZYLDTBBEDNXFMD77RJVZYVIDOK","short_pith_number":"pith:ZYLDTBBE","schema_version":"1.0","canonical_sha256":"ce163984241b6e560fff8a6b9c550372bd88fc1940e45b7d03f26f947984a38c","source":{"kind":"arxiv","id":"1406.2538","version":1},"attestation_state":"computed","paper":{"title":"FrameNet CNL: a Knowledge Representation and Information Extraction Language","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.IR","cs.LG"],"primary_cat":"cs.CL","authors_text":"Guntis Barzdins","submitted_at":"2014-06-10T13:16:36Z","abstract_excerpt":"The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL. The framework is used on natural language documents and represents the extracted knowledge in a tailor-made Frame-ontology from which unambiguous FrameNet-CNL paraphrase text can be generated automatically in multiple languages. This approach brings together the fields of information extraction and CNL, because a source text can be considered belonging to FrameNet-CNL, if information extraction parser produces the correct knowledge representation as a result. We describe a st"},"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":"1406.2538","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2014-06-10T13:16:36Z","cross_cats_sorted":["cs.AI","cs.IR","cs.LG"],"title_canon_sha256":"ff0049a5b4476976fb80eaf1fea83554db635bf53042307ae019d14061d4e759","abstract_canon_sha256":"0f6c14dc390f087ccb0040d47e007fed91e3429d749b548d83c7f861f68ba18b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:50:01.496072Z","signature_b64":"NYyvk1Ovd8Xq0q4P15E07I1jEmUN0TKpaAHMpD606Qj2dpj7kGeuwKuTmvHfn3fTMPKBqVdhL2A5JLcVjF4NAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ce163984241b6e560fff8a6b9c550372bd88fc1940e45b7d03f26f947984a38c","last_reissued_at":"2026-05-18T02:50:01.495578Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:50:01.495578Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"FrameNet CNL: a Knowledge Representation and Information Extraction Language","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.IR","cs.LG"],"primary_cat":"cs.CL","authors_text":"Guntis Barzdins","submitted_at":"2014-06-10T13:16:36Z","abstract_excerpt":"The paper presents a FrameNet-based information extraction and knowledge representation framework, called FrameNet-CNL. The framework is used on natural language documents and represents the extracted knowledge in a tailor-made Frame-ontology from which unambiguous FrameNet-CNL paraphrase text can be generated automatically in multiple languages. This approach brings together the fields of information extraction and CNL, because a source text can be considered belonging to FrameNet-CNL, if information extraction parser produces the correct knowledge representation as a result. We describe a st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1406.2538","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":"1406.2538","created_at":"2026-05-18T02:50:01.495647+00:00"},{"alias_kind":"arxiv_version","alias_value":"1406.2538v1","created_at":"2026-05-18T02:50:01.495647+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1406.2538","created_at":"2026-05-18T02:50:01.495647+00:00"},{"alias_kind":"pith_short_12","alias_value":"ZYLDTBBEDNXF","created_at":"2026-05-18T12:28:59.999130+00:00"},{"alias_kind":"pith_short_16","alias_value":"ZYLDTBBEDNXFMD77","created_at":"2026-05-18T12:28:59.999130+00:00"},{"alias_kind":"pith_short_8","alias_value":"ZYLDTBBE","created_at":"2026-05-18T12:28:59.999130+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/ZYLDTBBEDNXFMD77RJVZYVIDOK","json":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK.json","graph_json":"https://pith.science/api/pith-number/ZYLDTBBEDNXFMD77RJVZYVIDOK/graph.json","events_json":"https://pith.science/api/pith-number/ZYLDTBBEDNXFMD77RJVZYVIDOK/events.json","paper":"https://pith.science/paper/ZYLDTBBE"},"agent_actions":{"view_html":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK","download_json":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK.json","view_paper":"https://pith.science/paper/ZYLDTBBE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1406.2538&json=true","fetch_graph":"https://pith.science/api/pith-number/ZYLDTBBEDNXFMD77RJVZYVIDOK/graph.json","fetch_events":"https://pith.science/api/pith-number/ZYLDTBBEDNXFMD77RJVZYVIDOK/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK/action/storage_attestation","attest_author":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK/action/author_attestation","sign_citation":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK/action/citation_signature","submit_replication":"https://pith.science/pith/ZYLDTBBEDNXFMD77RJVZYVIDOK/action/replication_record"}},"created_at":"2026-05-18T02:50:01.495647+00:00","updated_at":"2026-05-18T02:50:01.495647+00:00"}