{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:6MFHDHLHC5DQQ4D56SXAXHCDEH","short_pith_number":"pith:6MFHDHLH","canonical_record":{"source":{"id":"2205.04504","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2022-05-09T18:19:51Z","cross_cats_sorted":[],"title_canon_sha256":"9f0aa8ed11acba10d8c9f8c0ed90cadd4c573f9649a6e0248bbe450ff95fa649","abstract_canon_sha256":"dfcbeba81a46da6509d749a946706eafad2271e4391cae383b2ab7feb9a49e10"},"schema_version":"1.0"},"canonical_sha256":"f30a719d67174708707df4ae0b9c4321ccfb8c25fec9eac6a31adb436b7ab2f6","source":{"kind":"arxiv","id":"2205.04504","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.04504","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"arxiv_version","alias_value":"2205.04504v1","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.04504","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_12","alias_value":"6MFHDHLHC5DQ","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_16","alias_value":"6MFHDHLHC5DQQ4D5","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_8","alias_value":"6MFHDHLH","created_at":"2026-07-05T04:21:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:6MFHDHLHC5DQQ4D56SXAXHCDEH","target":"record","payload":{"canonical_record":{"source":{"id":"2205.04504","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2022-05-09T18:19:51Z","cross_cats_sorted":[],"title_canon_sha256":"9f0aa8ed11acba10d8c9f8c0ed90cadd4c573f9649a6e0248bbe450ff95fa649","abstract_canon_sha256":"dfcbeba81a46da6509d749a946706eafad2271e4391cae383b2ab7feb9a49e10"},"schema_version":"1.0"},"canonical_sha256":"f30a719d67174708707df4ae0b9c4321ccfb8c25fec9eac6a31adb436b7ab2f6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:21:37.039900Z","signature_b64":"e73eKw3Aawvhyb0f91MoQQgImYn4rKJgPR4r+YPvpijAd3s5LuUzG31h5mVx3SIlZD61t+YlS4wPRIi9teo9DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f30a719d67174708707df4ae0b9c4321ccfb8c25fec9eac6a31adb436b7ab2f6","last_reissued_at":"2026-07-05T04:21:37.039372Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:21:37.039372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.04504","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":"2026-07-05T04:21:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rDV6kpgNpK+nBMJ+kKGPdZDbuVFFliJL2nhEhtWOe6VcuVYZoZEINC3w86BoBHm2ei8/lmiOTsgRRSAjBWOnAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T09:29:35.691454Z"},"content_sha256":"a24b57b23fab0e51050c9391b4b0592d3d75e2c961eeafb551b0b9b65ad76e53","schema_version":"1.0","event_id":"sha256:a24b57b23fab0e51050c9391b4b0592d3d75e2c961eeafb551b0b9b65ad76e53"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:6MFHDHLHC5DQQ4D56SXAXHCDEH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TinyGenius: Intertwining Natural Language Processing with Microtask Crowdsourcing for Scholarly Knowledge Graph Creation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DL","authors_text":"Allard Oelen, Markus Stocker, S\\\"oren Auer","submitted_at":"2022-05-09T18:19:51Z","abstract_excerpt":"As the number of published scholarly articles grows steadily each year, new methods are needed to organize scholarly knowledge so that it can be more efficiently discovered and used. Natural Language Processing (NLP) techniques are able to autonomously process scholarly articles at scale and to create machine readable representations of the article content. However, autonomous NLP methods are by far not sufficiently accurate to create a high-quality knowledge graph. Yet quality is crucial for the graph to be useful in practice. We present TinyGenius, a methodology to validate NLP-extracted sch"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.04504","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2205.04504/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T04:21:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eI4tW9jPFnnQJgj/4mOSavV/XvLm28Yl1ruQHpkW0vCKFTikV8zqpcitaBpYATuGk32Bxx+Cjhkh9KaqK6FbAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T09:29:35.691827Z"},"content_sha256":"8fcdbcf405b65dd17d4449650a9ced7df5cd34be4cee54d82b228fc342a3b3be","schema_version":"1.0","event_id":"sha256:8fcdbcf405b65dd17d4449650a9ced7df5cd34be4cee54d82b228fc342a3b3be"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/bundle.json","state_url":"https://pith.science/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/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":"2026-07-13T09:29:35Z","links":{"resolver":"https://pith.science/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH","bundle":"https://pith.science/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/bundle.json","state":"https://pith.science/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6MFHDHLHC5DQQ4D56SXAXHCDEH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:6MFHDHLHC5DQQ4D56SXAXHCDEH","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":"dfcbeba81a46da6509d749a946706eafad2271e4391cae383b2ab7feb9a49e10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2022-05-09T18:19:51Z","title_canon_sha256":"9f0aa8ed11acba10d8c9f8c0ed90cadd4c573f9649a6e0248bbe450ff95fa649"},"schema_version":"1.0","source":{"id":"2205.04504","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.04504","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"arxiv_version","alias_value":"2205.04504v1","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.04504","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_12","alias_value":"6MFHDHLHC5DQ","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_16","alias_value":"6MFHDHLHC5DQQ4D5","created_at":"2026-07-05T04:21:37Z"},{"alias_kind":"pith_short_8","alias_value":"6MFHDHLH","created_at":"2026-07-05T04:21:37Z"}],"graph_snapshots":[{"event_id":"sha256:8fcdbcf405b65dd17d4449650a9ced7df5cd34be4cee54d82b228fc342a3b3be","target":"graph","created_at":"2026-07-05T04:21:37Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2205.04504/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As the number of published scholarly articles grows steadily each year, new methods are needed to organize scholarly knowledge so that it can be more efficiently discovered and used. Natural Language Processing (NLP) techniques are able to autonomously process scholarly articles at scale and to create machine readable representations of the article content. However, autonomous NLP methods are by far not sufficiently accurate to create a high-quality knowledge graph. Yet quality is crucial for the graph to be useful in practice. We present TinyGenius, a methodology to validate NLP-extracted sch","authors_text":"Allard Oelen, Markus Stocker, S\\\"oren Auer","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2022-05-09T18:19:51Z","title":"TinyGenius: Intertwining Natural Language Processing with Microtask Crowdsourcing for Scholarly Knowledge Graph Creation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.04504","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:a24b57b23fab0e51050c9391b4b0592d3d75e2c961eeafb551b0b9b65ad76e53","target":"record","created_at":"2026-07-05T04:21:37Z","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":"dfcbeba81a46da6509d749a946706eafad2271e4391cae383b2ab7feb9a49e10","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DL","submitted_at":"2022-05-09T18:19:51Z","title_canon_sha256":"9f0aa8ed11acba10d8c9f8c0ed90cadd4c573f9649a6e0248bbe450ff95fa649"},"schema_version":"1.0","source":{"id":"2205.04504","kind":"arxiv","version":1}},"canonical_sha256":"f30a719d67174708707df4ae0b9c4321ccfb8c25fec9eac6a31adb436b7ab2f6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f30a719d67174708707df4ae0b9c4321ccfb8c25fec9eac6a31adb436b7ab2f6","first_computed_at":"2026-07-05T04:21:37.039372Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:21:37.039372Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e73eKw3Aawvhyb0f91MoQQgImYn4rKJgPR4r+YPvpijAd3s5LuUzG31h5mVx3SIlZD61t+YlS4wPRIi9teo9DA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:21:37.039900Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.04504","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a24b57b23fab0e51050c9391b4b0592d3d75e2c961eeafb551b0b9b65ad76e53","sha256:8fcdbcf405b65dd17d4449650a9ced7df5cd34be4cee54d82b228fc342a3b3be"],"state_sha256":"90c789ee51b984aaa4630b14b265eb041df944a4d53c520b0f840d749c932c0f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GUK3m5j2i1RA7B5IfPSSmEeY/wktE2ZTgsSSm7zupmWIEq+xKULFMb67fXpNEswDoGCcz69BjJ5XOh3/qqdyBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T09:29:35.694128Z","bundle_sha256":"94e8b7a5bbdc62aefdb13bbbcb9b0428e72915fe059d8edd769e077396d3df57"}}