{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:OETNEQ3ZB6OW4D6WBZWADDT75E","short_pith_number":"pith:OETNEQ3Z","canonical_record":{"source":{"id":"1807.06270","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-17T08:13:19Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"95c4473c8f3c599d3da768aed3d20f9e0dc7613cf9048c09d455e5aa1a9d638b","abstract_canon_sha256":"316f2ca96f53ba739147bbd3593130ed9be55d4ef92993de9b4109727c579f94"},"schema_version":"1.0"},"canonical_sha256":"7126d243790f9d6e0fd60e6c018e7fe92076046dff4929c9db59b84266b73c38","source":{"kind":"arxiv","id":"1807.06270","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.06270","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"arxiv_version","alias_value":"1807.06270v1","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.06270","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"pith_short_12","alias_value":"OETNEQ3ZB6OW","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OETNEQ3ZB6OW4D6W","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OETNEQ3Z","created_at":"2026-05-18T12:32:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:OETNEQ3ZB6OW4D6WBZWADDT75E","target":"record","payload":{"canonical_record":{"source":{"id":"1807.06270","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-17T08:13:19Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"95c4473c8f3c599d3da768aed3d20f9e0dc7613cf9048c09d455e5aa1a9d638b","abstract_canon_sha256":"316f2ca96f53ba739147bbd3593130ed9be55d4ef92993de9b4109727c579f94"},"schema_version":"1.0"},"canonical_sha256":"7126d243790f9d6e0fd60e6c018e7fe92076046dff4929c9db59b84266b73c38","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:10:33.525413Z","signature_b64":"VkYrQ4h4LFPV/TTFFe+smq0gFEIBgt++zsFWvIylEnx/H/Bn0ee/yL6nulUoYGrNzAtc0ayHnvT2xIg9t0BmCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7126d243790f9d6e0fd60e6c018e7fe92076046dff4929c9db59b84266b73c38","last_reissued_at":"2026-05-18T00:10:33.524851Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:10:33.524851Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1807.06270","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":"2026-05-18T00:10:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UmctirfOCSgxUAr2c8rE6Fz3QdSnvqhBhOMm4nONA2ADMGyFZ1dqzGEXLqd733bqh0JPX/2i8hVmxhleQjjTDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T09:47:20.512896Z"},"content_sha256":"fb2c9e28567e90c4a2b6d437dd596214ae2436d96d45b9e199d4919a262488d1","schema_version":"1.0","event_id":"sha256:fb2c9e28567e90c4a2b6d437dd596214ae2436d96d45b9e199d4919a262488d1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:OETNEQ3ZB6OW4D6WBZWADDT75E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.CV","authors_text":"Animesh Prasad, Gundram Leifert, Herv\\'e D\\'ejean, Jean-Luc Meunier, Johannes Michael, Max Weidemann","submitted_at":"2018-07-17T08:13:19Z","abstract_excerpt":"In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robust reading competition. The information extraction is modeled as semantic labeling of the sequence across 2 set of labels. This can be achieved by sequentially or jointly applying handwritten text recognition (HTR) and named entity recognition (NER). We deploy a pipeline approach where first we use state-of-the-art HTR and use its output as input for NER. We show that given low resource setup and simple structure of t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.06270","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":"2026-05-18T00:10:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3e3FEV7JRBoqu5sd5sctsOFSWM5uT2AZ69F7Bxqio4gHLrfX0r2oUbc4sE8FUsqsP4ifONpBT1Zsk4T67DMWBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T09:47:20.513668Z"},"content_sha256":"703cbff25a12cb145a2c407b1f6370dbf397933d0fe2b2ff5cfcb7acaad34ee3","schema_version":"1.0","event_id":"sha256:703cbff25a12cb145a2c407b1f6370dbf397933d0fe2b2ff5cfcb7acaad34ee3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/bundle.json","state_url":"https://pith.science/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/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":"2026-05-26T09:47:20Z","links":{"resolver":"https://pith.science/pith/OETNEQ3ZB6OW4D6WBZWADDT75E","bundle":"https://pith.science/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/bundle.json","state":"https://pith.science/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OETNEQ3ZB6OW4D6WBZWADDT75E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:OETNEQ3ZB6OW4D6WBZWADDT75E","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":"316f2ca96f53ba739147bbd3593130ed9be55d4ef92993de9b4109727c579f94","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-17T08:13:19Z","title_canon_sha256":"95c4473c8f3c599d3da768aed3d20f9e0dc7613cf9048c09d455e5aa1a9d638b"},"schema_version":"1.0","source":{"id":"1807.06270","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1807.06270","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"arxiv_version","alias_value":"1807.06270v1","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1807.06270","created_at":"2026-05-18T00:10:33Z"},{"alias_kind":"pith_short_12","alias_value":"OETNEQ3ZB6OW","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_16","alias_value":"OETNEQ3ZB6OW4D6W","created_at":"2026-05-18T12:32:43Z"},{"alias_kind":"pith_short_8","alias_value":"OETNEQ3Z","created_at":"2026-05-18T12:32:43Z"}],"graph_snapshots":[{"event_id":"sha256:703cbff25a12cb145a2c407b1f6370dbf397933d0fe2b2ff5cfcb7acaad34ee3","target":"graph","created_at":"2026-05-18T00:10:33Z","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":"In this report, we present our findings from benchmarking experiments for information extraction on historical handwritten marriage records Esposalles from IEHHR - ICDAR 2017 robust reading competition. The information extraction is modeled as semantic labeling of the sequence across 2 set of labels. This can be achieved by sequentially or jointly applying handwritten text recognition (HTR) and named entity recognition (NER). We deploy a pipeline approach where first we use state-of-the-art HTR and use its output as input for NER. We show that given low resource setup and simple structure of t","authors_text":"Animesh Prasad, Gundram Leifert, Herv\\'e D\\'ejean, Jean-Luc Meunier, Johannes Michael, Max Weidemann","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-17T08:13:19Z","title":"Bench-Marking Information Extraction in Semi-Structured Historical Handwritten Records"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1807.06270","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:fb2c9e28567e90c4a2b6d437dd596214ae2436d96d45b9e199d4919a262488d1","target":"record","created_at":"2026-05-18T00:10:33Z","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":"316f2ca96f53ba739147bbd3593130ed9be55d4ef92993de9b4109727c579f94","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-07-17T08:13:19Z","title_canon_sha256":"95c4473c8f3c599d3da768aed3d20f9e0dc7613cf9048c09d455e5aa1a9d638b"},"schema_version":"1.0","source":{"id":"1807.06270","kind":"arxiv","version":1}},"canonical_sha256":"7126d243790f9d6e0fd60e6c018e7fe92076046dff4929c9db59b84266b73c38","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7126d243790f9d6e0fd60e6c018e7fe92076046dff4929c9db59b84266b73c38","first_computed_at":"2026-05-18T00:10:33.524851Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:10:33.524851Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VkYrQ4h4LFPV/TTFFe+smq0gFEIBgt++zsFWvIylEnx/H/Bn0ee/yL6nulUoYGrNzAtc0ayHnvT2xIg9t0BmCg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:10:33.525413Z","signed_message":"canonical_sha256_bytes"},"source_id":"1807.06270","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fb2c9e28567e90c4a2b6d437dd596214ae2436d96d45b9e199d4919a262488d1","sha256:703cbff25a12cb145a2c407b1f6370dbf397933d0fe2b2ff5cfcb7acaad34ee3"],"state_sha256":"97f10880eb3fa8a30fa5eb685c5a5283734bd3e7322d0d378c1f085eb826a9ef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eJvebWqXZndUvvUVVR3gyRDK9BtAe/VjEmWiVkJicRgafDvVI67pQ+RSQYBFS6SA8c5ElXkHd9JTB6qP4CnMDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T09:47:20.517716Z","bundle_sha256":"df3768c1f28b4de34a1ff6c0bdce7e3f77de37b5982761d20ca43cab9b790f99"}}