{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:7BAXLJFRZIFBEAEYEL2NI3XWLW","short_pith_number":"pith:7BAXLJFR","canonical_record":{"source":{"id":"1408.1928","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CL","submitted_at":"2014-08-08T17:49:02Z","cross_cats_sorted":[],"title_canon_sha256":"7674323b96fbbdec35f3aa36230d8c2e4e95ffa1f71dbef73936e0eace2991db","abstract_canon_sha256":"ba4868cdde12f8fda4db9c3d6cf233252f0af9ff3a4f7947b88a30c7d24c3102"},"schema_version":"1.0"},"canonical_sha256":"f84175a4b1ca0a12009822f4d46ef65d96a42e314f46ef8b244b649ddbd3bc72","source":{"kind":"arxiv","id":"1408.1928","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1408.1928","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"1408.1928v1","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1408.1928","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"7BAXLJFRZIFB","created_at":"2026-05-18T12:28:16Z"},{"alias_kind":"pith_short_16","alias_value":"7BAXLJFRZIFBEAEY","created_at":"2026-05-18T12:28:16Z"},{"alias_kind":"pith_short_8","alias_value":"7BAXLJFR","created_at":"2026-05-18T12:28:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:7BAXLJFRZIFBEAEYEL2NI3XWLW","target":"record","payload":{"canonical_record":{"source":{"id":"1408.1928","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CL","submitted_at":"2014-08-08T17:49:02Z","cross_cats_sorted":[],"title_canon_sha256":"7674323b96fbbdec35f3aa36230d8c2e4e95ffa1f71dbef73936e0eace2991db","abstract_canon_sha256":"ba4868cdde12f8fda4db9c3d6cf233252f0af9ff3a4f7947b88a30c7d24c3102"},"schema_version":"1.0"},"canonical_sha256":"f84175a4b1ca0a12009822f4d46ef65d96a42e314f46ef8b244b649ddbd3bc72","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:45:38.846162Z","signature_b64":"ZcG51+/y42DcbQtW66KeqPqDHNA28VovHhe1pD/rnQrXE6K168EkvhNbk3R37MgXcwkGevSMguLDK/O9EKo+Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f84175a4b1ca0a12009822f4d46ef65d96a42e314f46ef8b244b649ddbd3bc72","last_reissued_at":"2026-05-18T02:45:38.845738Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:45:38.845738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1408.1928","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":"2026-05-18T02:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ha9OvHBb+w3QRNBMW/dDiyFdwdN35Kvu7AB5TR3bKtegNDSwB2FwISHajlSN1ZVB3JxSqlR1vFHyt3CUTH4hCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:33:50.452630Z"},"content_sha256":"bd9c87cfa3d336fdfdd5e17af2bd9f91eda608a854b943f1dde58d1758d88a37","schema_version":"1.0","event_id":"sha256:bd9c87cfa3d336fdfdd5e17af2bd9f91eda608a854b943f1dde58d1758d88a37"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:7BAXLJFRZIFBEAEYEL2NI3XWLW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Microtask crowdsourcing for disease mention annotation in PubMed abstracts","license":"http://creativecommons.org/licenses/by/3.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Andrew I. Su, Benjamin M Good, Max Nanis","submitted_at":"2014-08-08T17:49:02Z","abstract_excerpt":"Identifying concepts and relationships in biomedical text enables knowledge to be applied in computational analyses. Many biological natural language process (BioNLP) projects attempt to address this challenge, but the state of the art in BioNLP still leaves much room for improvement. Progress in BioNLP research depends on large, annotated corpora for evaluating information extraction systems and training machine learning models. Traditionally, such corpora are created by small numbers of expert annotators often working over extended periods of time. Recent studies have shown that workers on m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1408.1928","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":"2026-05-18T02:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qYeTtOJey0c19qSwoVktLfECuT+dbtOBNzauDkHp3NaRXFUTKB6Mnw7GECOLoic2X1OEKide3ksyGeLyeo1uAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-31T01:33:50.453064Z"},"content_sha256":"e5b9a42af696ab8199bd45f2a9ca3e70e70526a9813d67d6853a495c33049c5c","schema_version":"1.0","event_id":"sha256:e5b9a42af696ab8199bd45f2a9ca3e70e70526a9813d67d6853a495c33049c5c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/bundle.json","state_url":"https://pith.science/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/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":"2026-05-31T01:33:50Z","links":{"resolver":"https://pith.science/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW","bundle":"https://pith.science/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/bundle.json","state":"https://pith.science/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7BAXLJFRZIFBEAEYEL2NI3XWLW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:7BAXLJFRZIFBEAEYEL2NI3XWLW","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":"ba4868cdde12f8fda4db9c3d6cf233252f0af9ff3a4f7947b88a30c7d24c3102","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CL","submitted_at":"2014-08-08T17:49:02Z","title_canon_sha256":"7674323b96fbbdec35f3aa36230d8c2e4e95ffa1f71dbef73936e0eace2991db"},"schema_version":"1.0","source":{"id":"1408.1928","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1408.1928","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"1408.1928v1","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1408.1928","created_at":"2026-05-18T02:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"7BAXLJFRZIFB","created_at":"2026-05-18T12:28:16Z"},{"alias_kind":"pith_short_16","alias_value":"7BAXLJFRZIFBEAEY","created_at":"2026-05-18T12:28:16Z"},{"alias_kind":"pith_short_8","alias_value":"7BAXLJFR","created_at":"2026-05-18T12:28:16Z"}],"graph_snapshots":[{"event_id":"sha256:e5b9a42af696ab8199bd45f2a9ca3e70e70526a9813d67d6853a495c33049c5c","target":"graph","created_at":"2026-05-18T02:45:38Z","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":"Identifying concepts and relationships in biomedical text enables knowledge to be applied in computational analyses. Many biological natural language process (BioNLP) projects attempt to address this challenge, but the state of the art in BioNLP still leaves much room for improvement. Progress in BioNLP research depends on large, annotated corpora for evaluating information extraction systems and training machine learning models. Traditionally, such corpora are created by small numbers of expert annotators often working over extended periods of time. Recent studies have shown that workers on m","authors_text":"Andrew I. Su, Benjamin M Good, Max Nanis","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CL","submitted_at":"2014-08-08T17:49:02Z","title":"Microtask crowdsourcing for disease mention annotation in PubMed abstracts"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1408.1928","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:bd9c87cfa3d336fdfdd5e17af2bd9f91eda608a854b943f1dde58d1758d88a37","target":"record","created_at":"2026-05-18T02:45:38Z","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":"ba4868cdde12f8fda4db9c3d6cf233252f0af9ff3a4f7947b88a30c7d24c3102","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/3.0/","primary_cat":"cs.CL","submitted_at":"2014-08-08T17:49:02Z","title_canon_sha256":"7674323b96fbbdec35f3aa36230d8c2e4e95ffa1f71dbef73936e0eace2991db"},"schema_version":"1.0","source":{"id":"1408.1928","kind":"arxiv","version":1}},"canonical_sha256":"f84175a4b1ca0a12009822f4d46ef65d96a42e314f46ef8b244b649ddbd3bc72","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f84175a4b1ca0a12009822f4d46ef65d96a42e314f46ef8b244b649ddbd3bc72","first_computed_at":"2026-05-18T02:45:38.845738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:45:38.845738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZcG51+/y42DcbQtW66KeqPqDHNA28VovHhe1pD/rnQrXE6K168EkvhNbk3R37MgXcwkGevSMguLDK/O9EKo+Dw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:45:38.846162Z","signed_message":"canonical_sha256_bytes"},"source_id":"1408.1928","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bd9c87cfa3d336fdfdd5e17af2bd9f91eda608a854b943f1dde58d1758d88a37","sha256:e5b9a42af696ab8199bd45f2a9ca3e70e70526a9813d67d6853a495c33049c5c"],"state_sha256":"74e20645c096473581c84bf2e833d9fbe4be5b9fe97b46a43bf270e1f4eb537a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aGIzTg9ROGjkrGoXpolkTO6eOUUHo8Eps2CR2/8+6Gx6x1RHt2V+nrc3jJSnmkRrz1cRyA5316mjNKV1XnQGDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-31T01:33:50.456218Z","bundle_sha256":"b94e82d8e5f8c54b9a9c05ec2cad5743a1d64f2890b7d618cbb0f2d200166d4b"}}