{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:ECMB5TKWPN2VXMRWU67HGKICXL","short_pith_number":"pith:ECMB5TKW","schema_version":"1.0","canonical_sha256":"20981ecd567b755bb236a7be732902bac44187f9bb90480aa21bbca3030802a8","source":{"kind":"arxiv","id":"1904.02357","version":3},"attestation_state":"computed","paper":{"title":"Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Haining Feng, Nanyun Peng, Seraphina Goldfarb-Tarrant","submitted_at":"2019-04-04T05:42:53Z","abstract_excerpt":"Story composition is a challenging problem for machines and even for humans. We present a neural narrative generation system that interacts with humans to generate stories. Our system has different levels of human interaction, which enables us to understand at what stage of story-writing human collaboration is most productive, both to improving story quality and human engagement in the writing process. We compare different varieties of interaction in story-writing, story-planning, and diversity controls under time constraints, and show that increased types of human collaboration at both planni"},"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":"1904.02357","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-04T05:42:53Z","cross_cats_sorted":[],"title_canon_sha256":"367201742db27a8d4894f293346ba9fc177c96403af6b3a78650832f92877433","abstract_canon_sha256":"c2380715d2d18faaa5e3621fe3fdae4090dec4e6d566b0c3d3ce2a080a329c84"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:44:33.818566Z","signature_b64":"o0orkxA8o1JOLSo3eHgaFSJRSJIVGBNkecfXWhccORbPnJXFTKzqDaL7Xgae0Wil4WpvzRVa8CYwsXQ1XjAqDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"20981ecd567b755bb236a7be732902bac44187f9bb90480aa21bbca3030802a8","last_reissued_at":"2026-05-17T23:44:33.818098Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:44:33.818098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Haining Feng, Nanyun Peng, Seraphina Goldfarb-Tarrant","submitted_at":"2019-04-04T05:42:53Z","abstract_excerpt":"Story composition is a challenging problem for machines and even for humans. We present a neural narrative generation system that interacts with humans to generate stories. Our system has different levels of human interaction, which enables us to understand at what stage of story-writing human collaboration is most productive, both to improving story quality and human engagement in the writing process. We compare different varieties of interaction in story-writing, story-planning, and diversity controls under time constraints, and show that increased types of human collaboration at both planni"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.02357","kind":"arxiv","version":3},"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":"1904.02357","created_at":"2026-05-17T23:44:33.818169+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.02357v3","created_at":"2026-05-17T23:44:33.818169+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.02357","created_at":"2026-05-17T23:44:33.818169+00:00"},{"alias_kind":"pith_short_12","alias_value":"ECMB5TKWPN2V","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"ECMB5TKWPN2VXMRW","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"ECMB5TKW","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2506.04180","citing_title":"SuperWriter: Reflection-Driven Long-Form Generation with Large Language Models","ref_index":17,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL","json":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL.json","graph_json":"https://pith.science/api/pith-number/ECMB5TKWPN2VXMRWU67HGKICXL/graph.json","events_json":"https://pith.science/api/pith-number/ECMB5TKWPN2VXMRWU67HGKICXL/events.json","paper":"https://pith.science/paper/ECMB5TKW"},"agent_actions":{"view_html":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL","download_json":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL.json","view_paper":"https://pith.science/paper/ECMB5TKW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.02357&json=true","fetch_graph":"https://pith.science/api/pith-number/ECMB5TKWPN2VXMRWU67HGKICXL/graph.json","fetch_events":"https://pith.science/api/pith-number/ECMB5TKWPN2VXMRWU67HGKICXL/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL/action/storage_attestation","attest_author":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL/action/author_attestation","sign_citation":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL/action/citation_signature","submit_replication":"https://pith.science/pith/ECMB5TKWPN2VXMRWU67HGKICXL/action/replication_record"}},"created_at":"2026-05-17T23:44:33.818169+00:00","updated_at":"2026-05-17T23:44:33.818169+00:00"}