{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:FGCTLPHWUZ2Q4IJVAYMX4JD2P7","short_pith_number":"pith:FGCTLPHW","canonical_record":{"source":{"id":"1904.04458","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-09T04:09:45Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"88f39e65e9b1dc5e55a4e861883a0cd41af3c13523065c987bad59982e94682a","abstract_canon_sha256":"b0c696308e3956db999cdad661e8cfe5bf3626a18e79433a88353e96c60dc715"},"schema_version":"1.0"},"canonical_sha256":"298535bcf6a6750e213506197e247a7fe239be4cdf6a0fa73ab93f739e4847f9","source":{"kind":"arxiv","id":"1904.04458","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04458","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04458v2","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04458","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"pith_short_12","alias_value":"FGCTLPHWUZ2Q","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FGCTLPHWUZ2Q4IJV","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FGCTLPHW","created_at":"2026-05-18T12:33:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:FGCTLPHWUZ2Q4IJVAYMX4JD2P7","target":"record","payload":{"canonical_record":{"source":{"id":"1904.04458","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-09T04:09:45Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"88f39e65e9b1dc5e55a4e861883a0cd41af3c13523065c987bad59982e94682a","abstract_canon_sha256":"b0c696308e3956db999cdad661e8cfe5bf3626a18e79433a88353e96c60dc715"},"schema_version":"1.0"},"canonical_sha256":"298535bcf6a6750e213506197e247a7fe239be4cdf6a0fa73ab93f739e4847f9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:42:41.851480Z","signature_b64":"ptaaTGQCX9qlIIStGH6e3q7XXJPxYctp6PfPIP7K+mozm3f7FXKiw99YTTKwJi2flwrmIi9JzYYwQsUOpOpuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"298535bcf6a6750e213506197e247a7fe239be4cdf6a0fa73ab93f739e4847f9","last_reissued_at":"2026-05-17T23:42:41.850782Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:42:41.850782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1904.04458","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:42:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OZwsOTaOpo+WJdYp6nF+tkJMLb3tUVVCogXfjmtq74Xdi3w/Nc4NrRife+vNea4TC6LcfFIOcUir8cg1wAWIBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T12:04:50.021363Z"},"content_sha256":"cddd57485d0c83277ec47b93c0c74412f6efb6fb93bc85435cd1a3e40d531506","schema_version":"1.0","event_id":"sha256:cddd57485d0c83277ec47b93c0c74412f6efb6fb93bc85435cd1a3e40d531506"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:FGCTLPHWUZ2Q4IJVAYMX4JD2P7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Knowledge-Augmented Language Model and its Application to Unsupervised Named-Entity Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Angli Liu, Jingfei Du, Veselin Stoyanov","submitted_at":"2019-04-09T04:09:45Z","abstract_excerpt":"Traditional language models are unable to efficiently model entity names observed in text. All but the most popular named entities appear infrequently in text providing insufficient context. Recent efforts have recognized that context can be generalized between entity names that share the same type (e.g., \\emph{person} or \\emph{location}) and have equipped language models with access to an external knowledge base (KB). Our Knowledge-Augmented Language Model (KALM) continues this line of work by augmenting a traditional model with a KB. Unlike previous methods, however, we train with an end-to-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04458","kind":"arxiv","version":2},"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":"2026-05-17T23:42:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8n5ExTx3ejYf1ZSMO6iHxVUuunC6e9Z82dniRqKzbB1z/OWxP6jrM1RlCho4Av2ln8+TZmnHuHtonQAXO4AKBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T12:04:50.021991Z"},"content_sha256":"79202a09d19f48bec85e0fed3c3ea6f3aea41c1dfebd52a4671175d44cad5e43","schema_version":"1.0","event_id":"sha256:79202a09d19f48bec85e0fed3c3ea6f3aea41c1dfebd52a4671175d44cad5e43"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/bundle.json","state_url":"https://pith.science/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/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":"2026-05-25T12:04:50Z","links":{"resolver":"https://pith.science/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7","bundle":"https://pith.science/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/bundle.json","state":"https://pith.science/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FGCTLPHWUZ2Q4IJVAYMX4JD2P7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:FGCTLPHWUZ2Q4IJVAYMX4JD2P7","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":"b0c696308e3956db999cdad661e8cfe5bf3626a18e79433a88353e96c60dc715","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-09T04:09:45Z","title_canon_sha256":"88f39e65e9b1dc5e55a4e861883a0cd41af3c13523065c987bad59982e94682a"},"schema_version":"1.0","source":{"id":"1904.04458","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1904.04458","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"arxiv_version","alias_value":"1904.04458v2","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.04458","created_at":"2026-05-17T23:42:41Z"},{"alias_kind":"pith_short_12","alias_value":"FGCTLPHWUZ2Q","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_16","alias_value":"FGCTLPHWUZ2Q4IJV","created_at":"2026-05-18T12:33:15Z"},{"alias_kind":"pith_short_8","alias_value":"FGCTLPHW","created_at":"2026-05-18T12:33:15Z"}],"graph_snapshots":[{"event_id":"sha256:79202a09d19f48bec85e0fed3c3ea6f3aea41c1dfebd52a4671175d44cad5e43","target":"graph","created_at":"2026-05-17T23:42:41Z","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":"Traditional language models are unable to efficiently model entity names observed in text. All but the most popular named entities appear infrequently in text providing insufficient context. Recent efforts have recognized that context can be generalized between entity names that share the same type (e.g., \\emph{person} or \\emph{location}) and have equipped language models with access to an external knowledge base (KB). Our Knowledge-Augmented Language Model (KALM) continues this line of work by augmenting a traditional model with a KB. Unlike previous methods, however, we train with an end-to-","authors_text":"Angli Liu, Jingfei Du, Veselin Stoyanov","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-09T04:09:45Z","title":"Knowledge-Augmented Language Model and its Application to Unsupervised Named-Entity Recognition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.04458","kind":"arxiv","version":2},"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:cddd57485d0c83277ec47b93c0c74412f6efb6fb93bc85435cd1a3e40d531506","target":"record","created_at":"2026-05-17T23:42:41Z","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":"b0c696308e3956db999cdad661e8cfe5bf3626a18e79433a88353e96c60dc715","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-04-09T04:09:45Z","title_canon_sha256":"88f39e65e9b1dc5e55a4e861883a0cd41af3c13523065c987bad59982e94682a"},"schema_version":"1.0","source":{"id":"1904.04458","kind":"arxiv","version":2}},"canonical_sha256":"298535bcf6a6750e213506197e247a7fe239be4cdf6a0fa73ab93f739e4847f9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"298535bcf6a6750e213506197e247a7fe239be4cdf6a0fa73ab93f739e4847f9","first_computed_at":"2026-05-17T23:42:41.850782Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:42:41.850782Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ptaaTGQCX9qlIIStGH6e3q7XXJPxYctp6PfPIP7K+mozm3f7FXKiw99YTTKwJi2flwrmIi9JzYYwQsUOpOpuCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:42:41.851480Z","signed_message":"canonical_sha256_bytes"},"source_id":"1904.04458","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cddd57485d0c83277ec47b93c0c74412f6efb6fb93bc85435cd1a3e40d531506","sha256:79202a09d19f48bec85e0fed3c3ea6f3aea41c1dfebd52a4671175d44cad5e43"],"state_sha256":"a9d4c677653c7969037c5cbcec58b40524ad2e6ca4e5aaabef1f9addc6a3723c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mpP+yU3zwt/Sc6zwDWP4uBw+mdtv97XM00kWMjtDvr0ADzPLDC6+qlTXPz2vLw6R2PYUZFa3jFOtyALeTi3DAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T12:04:50.025453Z","bundle_sha256":"32eec081cc0de8f282f40b93b8905942c4db6a16a5a1533aef46ef57b3a09bbf"}}