{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:S22OIKL3WA7NHW2PPOGRZCRU6G","short_pith_number":"pith:S22OIKL3","schema_version":"1.0","canonical_sha256":"96b4e4297bb03ed3db4f7b8d1c8a34f18796ecde4bba227ed0c734f35922aa5e","source":{"kind":"arxiv","id":"1709.05308","version":1},"attestation_state":"computed","paper":{"title":"Harvesting Creative Templates for Generating Stylistically Varied Restaurant Reviews","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Marilyn Walker, Sheideh Homayon, Shereen Oraby","submitted_at":"2017-09-15T16:59:20Z","abstract_excerpt":"Many of the creative and figurative elements that make language exciting are lost in translation in current natural language generation engines. In this paper, we explore a method to harvest templates from positive and negative reviews in the restaurant domain, with the goal of vastly expanding the types of stylistic variation available to the natural language generator. We learn hyperbolic adjective patterns that are representative of the strongly-valenced expressive language commonly used in either positive or negative reviews. We then identify and delexicalize entities, and use heuristics t"},"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":"1709.05308","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-09-15T16:59:20Z","cross_cats_sorted":[],"title_canon_sha256":"b65704d628c85acbc33878f63d47e84810b9870eb88f6a0158313c6637345f6d","abstract_canon_sha256":"f4b2f464ab875e91978d9cc1e3a499286b50bf51b543c4cd9bfd016e524793e2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:06.013759Z","signature_b64":"ryWwC9jH8TlZCZKtS5HTOXs0d5GeFeTnMW4qeVDYdvMmbc07DL3m12pOaUUmyTPK+qxWMYY60Txzy/sNgrK2Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"96b4e4297bb03ed3db4f7b8d1c8a34f18796ecde4bba227ed0c734f35922aa5e","last_reissued_at":"2026-05-18T00:35:06.013100Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:06.013100Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Harvesting Creative Templates for Generating Stylistically Varied Restaurant Reviews","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Marilyn Walker, Sheideh Homayon, Shereen Oraby","submitted_at":"2017-09-15T16:59:20Z","abstract_excerpt":"Many of the creative and figurative elements that make language exciting are lost in translation in current natural language generation engines. In this paper, we explore a method to harvest templates from positive and negative reviews in the restaurant domain, with the goal of vastly expanding the types of stylistic variation available to the natural language generator. We learn hyperbolic adjective patterns that are representative of the strongly-valenced expressive language commonly used in either positive or negative reviews. We then identify and delexicalize entities, and use heuristics t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.05308","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":"1709.05308","created_at":"2026-05-18T00:35:06.013224+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.05308v1","created_at":"2026-05-18T00:35:06.013224+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.05308","created_at":"2026-05-18T00:35:06.013224+00:00"},{"alias_kind":"pith_short_12","alias_value":"S22OIKL3WA7N","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_16","alias_value":"S22OIKL3WA7NHW2P","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_8","alias_value":"S22OIKL3","created_at":"2026-05-18T12:31:43.269735+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/S22OIKL3WA7NHW2PPOGRZCRU6G","json":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G.json","graph_json":"https://pith.science/api/pith-number/S22OIKL3WA7NHW2PPOGRZCRU6G/graph.json","events_json":"https://pith.science/api/pith-number/S22OIKL3WA7NHW2PPOGRZCRU6G/events.json","paper":"https://pith.science/paper/S22OIKL3"},"agent_actions":{"view_html":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G","download_json":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G.json","view_paper":"https://pith.science/paper/S22OIKL3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.05308&json=true","fetch_graph":"https://pith.science/api/pith-number/S22OIKL3WA7NHW2PPOGRZCRU6G/graph.json","fetch_events":"https://pith.science/api/pith-number/S22OIKL3WA7NHW2PPOGRZCRU6G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G/action/storage_attestation","attest_author":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G/action/author_attestation","sign_citation":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G/action/citation_signature","submit_replication":"https://pith.science/pith/S22OIKL3WA7NHW2PPOGRZCRU6G/action/replication_record"}},"created_at":"2026-05-18T00:35:06.013224+00:00","updated_at":"2026-05-18T00:35:06.013224+00:00"}