{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:AMGX642SPVNV42TANYHFOWQZB6","short_pith_number":"pith:AMGX642S","schema_version":"1.0","canonical_sha256":"030d7f73527d5b5e6a606e0e575a190f99924851899b1527f2c8ca40c446dc43","source":{"kind":"arxiv","id":"1712.09827","version":1},"attestation_state":"computed","paper":{"title":"A Syntactic Approach to Domain-Specific Automatic Question Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Guy Danon, Mark Last","submitted_at":"2017-12-28T11:15:30Z","abstract_excerpt":"Factoid questions are questions that require short fact-based answers. Automatic generation (AQG) of factoid questions from a given text can contribute to educational activities, interactive question answering systems, search engines, and other applications. The goal of our research is to generate factoid source-question-answer triplets based on a specific domain. We propose a four-component pipeline, which obtains as input a training corpus of domain-specific documents, along with a set of declarative sentences from the same domain, and generates as output a set of factoid questions that refe"},"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":"1712.09827","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-12-28T11:15:30Z","cross_cats_sorted":[],"title_canon_sha256":"095872b3b2eefac84a43b8436ae49dfdc8a7411fb677414ff2da0e5fc7de0583","abstract_canon_sha256":"50479f39cbcc9ed1afd48f1c3089b6141a6d8228f2b2ff55349deaeca3dd685c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:27:05.453697Z","signature_b64":"jMRYXTPFFUr79oaViRtGafhKiNKcNMVDIVN+mCvIWWSwRNkB2kSKb6w1o0r4/fTnx+5fTwh09VcpHO0FsTJ6DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"030d7f73527d5b5e6a606e0e575a190f99924851899b1527f2c8ca40c446dc43","last_reissued_at":"2026-05-18T00:27:05.453171Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:27:05.453171Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Syntactic Approach to Domain-Specific Automatic Question Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Guy Danon, Mark Last","submitted_at":"2017-12-28T11:15:30Z","abstract_excerpt":"Factoid questions are questions that require short fact-based answers. Automatic generation (AQG) of factoid questions from a given text can contribute to educational activities, interactive question answering systems, search engines, and other applications. The goal of our research is to generate factoid source-question-answer triplets based on a specific domain. We propose a four-component pipeline, which obtains as input a training corpus of domain-specific documents, along with a set of declarative sentences from the same domain, and generates as output a set of factoid questions that refe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1712.09827","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":"1712.09827","created_at":"2026-05-18T00:27:05.453247+00:00"},{"alias_kind":"arxiv_version","alias_value":"1712.09827v1","created_at":"2026-05-18T00:27:05.453247+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1712.09827","created_at":"2026-05-18T00:27:05.453247+00:00"},{"alias_kind":"pith_short_12","alias_value":"AMGX642SPVNV","created_at":"2026-05-18T12:31:05.417338+00:00"},{"alias_kind":"pith_short_16","alias_value":"AMGX642SPVNV42TA","created_at":"2026-05-18T12:31:05.417338+00:00"},{"alias_kind":"pith_short_8","alias_value":"AMGX642S","created_at":"2026-05-18T12:31:05.417338+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/AMGX642SPVNV42TANYHFOWQZB6","json":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6.json","graph_json":"https://pith.science/api/pith-number/AMGX642SPVNV42TANYHFOWQZB6/graph.json","events_json":"https://pith.science/api/pith-number/AMGX642SPVNV42TANYHFOWQZB6/events.json","paper":"https://pith.science/paper/AMGX642S"},"agent_actions":{"view_html":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6","download_json":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6.json","view_paper":"https://pith.science/paper/AMGX642S","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1712.09827&json=true","fetch_graph":"https://pith.science/api/pith-number/AMGX642SPVNV42TANYHFOWQZB6/graph.json","fetch_events":"https://pith.science/api/pith-number/AMGX642SPVNV42TANYHFOWQZB6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6/action/storage_attestation","attest_author":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6/action/author_attestation","sign_citation":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6/action/citation_signature","submit_replication":"https://pith.science/pith/AMGX642SPVNV42TANYHFOWQZB6/action/replication_record"}},"created_at":"2026-05-18T00:27:05.453247+00:00","updated_at":"2026-05-18T00:27:05.453247+00:00"}