{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2012:567W3NB3C3V5XZA5LU6PCOFOKQ","short_pith_number":"pith:567W3NB3","canonical_record":{"source":{"id":"1206.0377","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2012-06-02T13:11:17Z","cross_cats_sorted":["math.CO"],"title_canon_sha256":"878e5d6d2a50c887da67fde3122815faf2b781476178cee87307012bf43714d8","abstract_canon_sha256":"661a373d9665f93ddffbd130ff310b2236ceeebc8f28573c72d54607f11c2705"},"schema_version":"1.0"},"canonical_sha256":"efbf6db43b16ebdbe41d5d3cf138ae54194b86f18f3d34f8a8466f794f8e73e7","source":{"kind":"arxiv","id":"1206.0377","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1206.0377","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"arxiv_version","alias_value":"1206.0377v1","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1206.0377","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"pith_short_12","alias_value":"567W3NB3C3V5","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_16","alias_value":"567W3NB3C3V5XZA5","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_8","alias_value":"567W3NB3","created_at":"2026-05-18T12:26:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2012:567W3NB3C3V5XZA5LU6PCOFOKQ","target":"record","payload":{"canonical_record":{"source":{"id":"1206.0377","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2012-06-02T13:11:17Z","cross_cats_sorted":["math.CO"],"title_canon_sha256":"878e5d6d2a50c887da67fde3122815faf2b781476178cee87307012bf43714d8","abstract_canon_sha256":"661a373d9665f93ddffbd130ff310b2236ceeebc8f28573c72d54607f11c2705"},"schema_version":"1.0"},"canonical_sha256":"efbf6db43b16ebdbe41d5d3cf138ae54194b86f18f3d34f8a8466f794f8e73e7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T03:54:17.828796Z","signature_b64":"WLMUOyM9EVVLvXZRbvb2eBJWHsqhpuMEVmVIWBO0wa4JGSITJLZhJn/5MMJlMIEs5RQ05qoNTRsogA28flgZAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"efbf6db43b16ebdbe41d5d3cf138ae54194b86f18f3d34f8a8466f794f8e73e7","last_reissued_at":"2026-05-18T03:54:17.828103Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T03:54:17.828103Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1206.0377","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:54:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"z5etYJJo0A6alSIHyROORfUJK67MZDQGGXyJLC1lirLm5x8A5XLDmLSiy2anFVo79n+r+r4bBVLNiu1wG1PEBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T21:37:37.349033Z"},"content_sha256":"d5a26b0f32e8c80aaaf3dc80e67cbac41fc1958ec97bab74daed2bf5d29002b7","schema_version":"1.0","event_id":"sha256:d5a26b0f32e8c80aaaf3dc80e67cbac41fc1958ec97bab74daed2bf5d29002b7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2012:567W3NB3C3V5XZA5LU6PCOFOKQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Automated Word Puzzle Generation via Topic Dictionaries","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.CO"],"primary_cat":"cs.CL","authors_text":"Andras Lorincz, Balazs Pinter, Gyula Voros, Zoltan Szabo","submitted_at":"2012-06-02T13:11:17Z","abstract_excerpt":"We propose a general method for automated word puzzle generation. Contrary to previous approaches in this novel field, the presented method does not rely on highly structured datasets obtained with serious human annotation effort: it only needs an unstructured and unannotated corpus (i.e., document collection) as input. The method builds upon two additional pillars: (i) a topic model, which induces a topic dictionary from the input corpus (examples include e.g., latent semantic analysis, group-structured dictionaries or latent Dirichlet allocation), and (ii) a semantic similarity measure of wo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1206.0377","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T03:54:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KBrJRP+L8fVvgVoIT6J2Y+29rYjFI1B28YV7NjHonjCSofc8kF/4QjzYsEqlg5hzbAwvMLuQVUfb3/bNWsdCBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T21:37:37.349849Z"},"content_sha256":"38c1a53f7b7ba385a2db88e40773e358718bd84e0d5c0dc451b5009a7bf687d8","schema_version":"1.0","event_id":"sha256:38c1a53f7b7ba385a2db88e40773e358718bd84e0d5c0dc451b5009a7bf687d8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/bundle.json","state_url":"https://pith.science/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-30T21:37:37Z","links":{"resolver":"https://pith.science/pith/567W3NB3C3V5XZA5LU6PCOFOKQ","bundle":"https://pith.science/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/bundle.json","state":"https://pith.science/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/567W3NB3C3V5XZA5LU6PCOFOKQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2012:567W3NB3C3V5XZA5LU6PCOFOKQ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"661a373d9665f93ddffbd130ff310b2236ceeebc8f28573c72d54607f11c2705","cross_cats_sorted":["math.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2012-06-02T13:11:17Z","title_canon_sha256":"878e5d6d2a50c887da67fde3122815faf2b781476178cee87307012bf43714d8"},"schema_version":"1.0","source":{"id":"1206.0377","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1206.0377","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"arxiv_version","alias_value":"1206.0377v1","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1206.0377","created_at":"2026-05-18T03:54:17Z"},{"alias_kind":"pith_short_12","alias_value":"567W3NB3C3V5","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_16","alias_value":"567W3NB3C3V5XZA5","created_at":"2026-05-18T12:26:53Z"},{"alias_kind":"pith_short_8","alias_value":"567W3NB3","created_at":"2026-05-18T12:26:53Z"}],"graph_snapshots":[{"event_id":"sha256:38c1a53f7b7ba385a2db88e40773e358718bd84e0d5c0dc451b5009a7bf687d8","target":"graph","created_at":"2026-05-18T03:54:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We propose a general method for automated word puzzle generation. Contrary to previous approaches in this novel field, the presented method does not rely on highly structured datasets obtained with serious human annotation effort: it only needs an unstructured and unannotated corpus (i.e., document collection) as input. The method builds upon two additional pillars: (i) a topic model, which induces a topic dictionary from the input corpus (examples include e.g., latent semantic analysis, group-structured dictionaries or latent Dirichlet allocation), and (ii) a semantic similarity measure of wo","authors_text":"Andras Lorincz, Balazs Pinter, Gyula Voros, Zoltan Szabo","cross_cats":["math.CO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2012-06-02T13:11:17Z","title":"Automated Word Puzzle Generation via Topic Dictionaries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1206.0377","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d5a26b0f32e8c80aaaf3dc80e67cbac41fc1958ec97bab74daed2bf5d29002b7","target":"record","created_at":"2026-05-18T03:54:17Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"661a373d9665f93ddffbd130ff310b2236ceeebc8f28573c72d54607f11c2705","cross_cats_sorted":["math.CO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2012-06-02T13:11:17Z","title_canon_sha256":"878e5d6d2a50c887da67fde3122815faf2b781476178cee87307012bf43714d8"},"schema_version":"1.0","source":{"id":"1206.0377","kind":"arxiv","version":1}},"canonical_sha256":"efbf6db43b16ebdbe41d5d3cf138ae54194b86f18f3d34f8a8466f794f8e73e7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"efbf6db43b16ebdbe41d5d3cf138ae54194b86f18f3d34f8a8466f794f8e73e7","first_computed_at":"2026-05-18T03:54:17.828103Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T03:54:17.828103Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WLMUOyM9EVVLvXZRbvb2eBJWHsqhpuMEVmVIWBO0wa4JGSITJLZhJn/5MMJlMIEs5RQ05qoNTRsogA28flgZAw==","signature_status":"signed_v1","signed_at":"2026-05-18T03:54:17.828796Z","signed_message":"canonical_sha256_bytes"},"source_id":"1206.0377","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d5a26b0f32e8c80aaaf3dc80e67cbac41fc1958ec97bab74daed2bf5d29002b7","sha256:38c1a53f7b7ba385a2db88e40773e358718bd84e0d5c0dc451b5009a7bf687d8"],"state_sha256":"aff5baed72a8005d84b166b4fc57e1b7aa23a5a923a26dba57b4465b7d849783"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CnwAMAlidIy6oh97mdFhdmI6DyYv8JCuW7ofZon98GF5aruL9f9xR/PrgjH1j65CGgzLmiw7nu+1AzL/+kfaBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T21:37:37.354023Z","bundle_sha256":"5d16bac641bcbbb91f420cdc5733e5fa54b9043a3bfc699982c0af1c72f66297"}}