{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:WY4EKDWZBSU5OKSLSUEVWQP5ZB","short_pith_number":"pith:WY4EKDWZ","canonical_record":{"source":{"id":"2011.06727","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-11-13T02:29:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8b9b07d2c5128695699fd0f760c664538bb01914672d9ea742ac13c42a855a4e","abstract_canon_sha256":"7271561021a04c9e05f552cf626c83233ae259ebedc8a94f355dc6d33e633549"},"schema_version":"1.0"},"canonical_sha256":"b638450ed90ca9d72a4b95095b41fdc842dc49fd529fe1ec34347f572b7a4f84","source":{"kind":"arxiv","id":"2011.06727","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.06727","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"2011.06727v1","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.06727","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"WY4EKDWZBSU5","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_16","alias_value":"WY4EKDWZBSU5OKSL","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_8","alias_value":"WY4EKDWZ","created_at":"2026-07-05T01:51:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:WY4EKDWZBSU5OKSLSUEVWQP5ZB","target":"record","payload":{"canonical_record":{"source":{"id":"2011.06727","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-11-13T02:29:50Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"8b9b07d2c5128695699fd0f760c664538bb01914672d9ea742ac13c42a855a4e","abstract_canon_sha256":"7271561021a04c9e05f552cf626c83233ae259ebedc8a94f355dc6d33e633549"},"schema_version":"1.0"},"canonical_sha256":"b638450ed90ca9d72a4b95095b41fdc842dc49fd529fe1ec34347f572b7a4f84","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:51:24.552308Z","signature_b64":"nBNU8EXxwmA1a79j7p8fvLWFw6D6To0shJJhWN+WxD1gAECbSEAqh1vPAhq3PtK9noeXcuTpNDYlPln1EEABAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b638450ed90ca9d72a4b95095b41fdc842dc49fd529fe1ec34347f572b7a4f84","last_reissued_at":"2026-07-05T01:51:24.551925Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:51:24.551925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2011.06727","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":"2026-07-05T01:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s+2Xhxac8/Ba/A/nG4ZzCXqIvrJnT1yTKu29lpBuecIuOt/Y/2A/2g8CNZgzIeI4fyduShMld58HPVzi05eiAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T10:00:36.125584Z"},"content_sha256":"1665821d5f80640872803553137b27443b56faa9acc1494934b14d37bceab4a2","schema_version":"1.0","event_id":"sha256:1665821d5f80640872803553137b27443b56faa9acc1494934b14d37bceab4a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:WY4EKDWZBSU5OKSLSUEVWQP5ZB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey on Recent Advances in Sequence Labeling from Deep Learning Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Shanshan Feng, Sheng Jiang, Wei Wei, Xianling Mao, Zanbo Wang, Zhiyong He","submitted_at":"2020-11-13T02:29:50Z","abstract_excerpt":"Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, e.g., part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc. Though prevalent and effective in many downstream applications (e.g., information retrieval, question answering, and knowledge graph embedding), conventional sequence labeling approaches heavily rely on hand-crafted or language-specific features. Recently, deep learning has been employed for sequence labeling tasks due to its powerful capability in automatically learning complex features of instances and effectively yi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.06727","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/2011.06727/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":"2026-07-05T01:51:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jWssLcObIw+H6yWRdPs3m0GVwNVZ5XH44/PrNSfaML0JvS/hQ6nMHMo175SN9JG9LJLkOyIf27qMq0yv1TZJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T10:00:36.126120Z"},"content_sha256":"a1bdba552909dce064f231c919ddba4549f916de7371f08d4b25d55cd00eb143","schema_version":"1.0","event_id":"sha256:a1bdba552909dce064f231c919ddba4549f916de7371f08d4b25d55cd00eb143"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/bundle.json","state_url":"https://pith.science/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/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":"2026-08-03T10:00:36Z","links":{"resolver":"https://pith.science/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB","bundle":"https://pith.science/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/bundle.json","state":"https://pith.science/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WY4EKDWZBSU5OKSLSUEVWQP5ZB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:WY4EKDWZBSU5OKSLSUEVWQP5ZB","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":"7271561021a04c9e05f552cf626c83233ae259ebedc8a94f355dc6d33e633549","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-11-13T02:29:50Z","title_canon_sha256":"8b9b07d2c5128695699fd0f760c664538bb01914672d9ea742ac13c42a855a4e"},"schema_version":"1.0","source":{"id":"2011.06727","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2011.06727","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"arxiv_version","alias_value":"2011.06727v1","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2011.06727","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_12","alias_value":"WY4EKDWZBSU5","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_16","alias_value":"WY4EKDWZBSU5OKSL","created_at":"2026-07-05T01:51:24Z"},{"alias_kind":"pith_short_8","alias_value":"WY4EKDWZ","created_at":"2026-07-05T01:51:24Z"}],"graph_snapshots":[{"event_id":"sha256:a1bdba552909dce064f231c919ddba4549f916de7371f08d4b25d55cd00eb143","target":"graph","created_at":"2026-07-05T01:51:24Z","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/2011.06727/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sequence labeling (SL) is a fundamental research problem encompassing a variety of tasks, e.g., part-of-speech (POS) tagging, named entity recognition (NER), text chunking, etc. Though prevalent and effective in many downstream applications (e.g., information retrieval, question answering, and knowledge graph embedding), conventional sequence labeling approaches heavily rely on hand-crafted or language-specific features. Recently, deep learning has been employed for sequence labeling tasks due to its powerful capability in automatically learning complex features of instances and effectively yi","authors_text":"Shanshan Feng, Sheng Jiang, Wei Wei, Xianling Mao, Zanbo Wang, Zhiyong He","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-11-13T02:29:50Z","title":"A Survey on Recent Advances in Sequence Labeling from Deep Learning Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2011.06727","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":"sha256:1665821d5f80640872803553137b27443b56faa9acc1494934b14d37bceab4a2","target":"record","created_at":"2026-07-05T01:51:24Z","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":"7271561021a04c9e05f552cf626c83233ae259ebedc8a94f355dc6d33e633549","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-11-13T02:29:50Z","title_canon_sha256":"8b9b07d2c5128695699fd0f760c664538bb01914672d9ea742ac13c42a855a4e"},"schema_version":"1.0","source":{"id":"2011.06727","kind":"arxiv","version":1}},"canonical_sha256":"b638450ed90ca9d72a4b95095b41fdc842dc49fd529fe1ec34347f572b7a4f84","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b638450ed90ca9d72a4b95095b41fdc842dc49fd529fe1ec34347f572b7a4f84","first_computed_at":"2026-07-05T01:51:24.551925Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:51:24.551925Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nBNU8EXxwmA1a79j7p8fvLWFw6D6To0shJJhWN+WxD1gAECbSEAqh1vPAhq3PtK9noeXcuTpNDYlPln1EEABAA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:51:24.552308Z","signed_message":"canonical_sha256_bytes"},"source_id":"2011.06727","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1665821d5f80640872803553137b27443b56faa9acc1494934b14d37bceab4a2","sha256:a1bdba552909dce064f231c919ddba4549f916de7371f08d4b25d55cd00eb143"],"state_sha256":"f954707ec7744e5c2692970cae731ca12f6be45a9f1b66a4782b44f68bfc91ef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DVs0KzdFbSDCcjAL5lyeUtfls6ksQ91N59s7DpFWYsAMKsK8IyWuEQWu29X5+01e6qu/4HQ09tmt5s7B5GxWAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T10:00:36.129593Z","bundle_sha256":"9cb730f10451e3b053c883609960fe6ba325631c1e3de09e12edc038736822d7"}}