{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:VHFMYVK54JXSVTL6CNBNYTC6CK","short_pith_number":"pith:VHFMYVK5","canonical_record":{"source":{"id":"1704.01314","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-05T08:58:44Z","cross_cats_sorted":[],"title_canon_sha256":"68a4f37df8cea6ecca6212dec7044652a50656acec67ef39e6b861b4175f8f9c","abstract_canon_sha256":"c9d0047a0a4b6b485bceb6d4f2b4f3ae61273917382ab854dd8184d30661d8bd"},"schema_version":"1.0"},"canonical_sha256":"a9cacc555de26f2acd7e1342dc4c5e12b60db623d06a653407b28a6fab9bcfe4","source":{"kind":"arxiv","id":"1704.01314","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.01314","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"arxiv_version","alias_value":"1704.01314v3","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01314","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"pith_short_12","alias_value":"VHFMYVK54JXS","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VHFMYVK54JXSVTL6","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VHFMYVK5","created_at":"2026-05-18T12:31:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:VHFMYVK54JXSVTL6CNBNYTC6CK","target":"record","payload":{"canonical_record":{"source":{"id":"1704.01314","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-05T08:58:44Z","cross_cats_sorted":[],"title_canon_sha256":"68a4f37df8cea6ecca6212dec7044652a50656acec67ef39e6b861b4175f8f9c","abstract_canon_sha256":"c9d0047a0a4b6b485bceb6d4f2b4f3ae61273917382ab854dd8184d30661d8bd"},"schema_version":"1.0"},"canonical_sha256":"a9cacc555de26f2acd7e1342dc4c5e12b60db623d06a653407b28a6fab9bcfe4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:35:34.159601Z","signature_b64":"h/RymHsI0sgYK8yXOvGIdFkV0ivt3rFMsZ5s8AncfDTw+B/OhS3DPEkxkvU4ZkHPoOWTAjJ/2nE3wOGL0/VsBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a9cacc555de26f2acd7e1342dc4c5e12b60db623d06a653407b28a6fab9bcfe4","last_reissued_at":"2026-05-18T00:35:34.159081Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:35:34.159081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1704.01314","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:35:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dlh8jojRAKso5SDhT3vxJ+35RVJ2FCKYVGwTsUNYQDE0JNoRa/KdAy3hb37GMlHe8cxrkG5jyLO7Wsh7FKfxBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T18:03:17.236258Z"},"content_sha256":"5c5afaa2b918a5b70a46986c9d7b018fc49f66dc82a6d838418646eb2b4e2236","schema_version":"1.0","event_id":"sha256:5c5afaa2b918a5b70a46986c9d7b018fc49f66dc82a6d838418646eb2b4e2236"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:VHFMYVK54JXSVTL6CNBNYTC6CK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Christian Hardmeier, Joakim Nivre, J\\\"org Tiedemann, Yan Shao","submitted_at":"2017-04-05T08:58:44Z","abstract_excerpt":"We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied with novel vector representations of Chinese characters that capture rich contextual information and lower-than-character level features. The proposed model is extensively evaluated and compared with a state-of-the-art tagger respectively on CTB5, CTB9 and UD Chinese. The experimental results indicate that our model is accurate and robust across datasets in different sizes, genres and annotation schemes. We obtain stat"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01314","kind":"arxiv","version":3},"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":"2026-05-18T00:35:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"psFbcGr6hVKSv81sv9rRYxhFjTjpNnnYwPMJ17HXtJ+5dJsb6s28DbmuMWjiLHr9OHIHMW0SysWBl4aPIrulBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T18:03:17.236653Z"},"content_sha256":"f6b8dfbbe1e137df01714325834ceb93c8d8854e0e1caa50ee348e2d598bd0cc","schema_version":"1.0","event_id":"sha256:f6b8dfbbe1e137df01714325834ceb93c8d8854e0e1caa50ee348e2d598bd0cc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/bundle.json","state_url":"https://pith.science/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/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":"2026-06-02T18:03:17Z","links":{"resolver":"https://pith.science/pith/VHFMYVK54JXSVTL6CNBNYTC6CK","bundle":"https://pith.science/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/bundle.json","state":"https://pith.science/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VHFMYVK54JXSVTL6CNBNYTC6CK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:VHFMYVK54JXSVTL6CNBNYTC6CK","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":"c9d0047a0a4b6b485bceb6d4f2b4f3ae61273917382ab854dd8184d30661d8bd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-05T08:58:44Z","title_canon_sha256":"68a4f37df8cea6ecca6212dec7044652a50656acec67ef39e6b861b4175f8f9c"},"schema_version":"1.0","source":{"id":"1704.01314","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.01314","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"arxiv_version","alias_value":"1704.01314v3","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.01314","created_at":"2026-05-18T00:35:34Z"},{"alias_kind":"pith_short_12","alias_value":"VHFMYVK54JXS","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_16","alias_value":"VHFMYVK54JXSVTL6","created_at":"2026-05-18T12:31:49Z"},{"alias_kind":"pith_short_8","alias_value":"VHFMYVK5","created_at":"2026-05-18T12:31:49Z"}],"graph_snapshots":[{"event_id":"sha256:f6b8dfbbe1e137df01714325834ceb93c8d8854e0e1caa50ee348e2d598bd0cc","target":"graph","created_at":"2026-05-18T00:35:34Z","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":"We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied with novel vector representations of Chinese characters that capture rich contextual information and lower-than-character level features. The proposed model is extensively evaluated and compared with a state-of-the-art tagger respectively on CTB5, CTB9 and UD Chinese. The experimental results indicate that our model is accurate and robust across datasets in different sizes, genres and annotation schemes. We obtain stat","authors_text":"Christian Hardmeier, Joakim Nivre, J\\\"org Tiedemann, Yan Shao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-05T08:58:44Z","title":"Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.01314","kind":"arxiv","version":3},"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":"sha256:5c5afaa2b918a5b70a46986c9d7b018fc49f66dc82a6d838418646eb2b4e2236","target":"record","created_at":"2026-05-18T00:35:34Z","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":"c9d0047a0a4b6b485bceb6d4f2b4f3ae61273917382ab854dd8184d30661d8bd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-04-05T08:58:44Z","title_canon_sha256":"68a4f37df8cea6ecca6212dec7044652a50656acec67ef39e6b861b4175f8f9c"},"schema_version":"1.0","source":{"id":"1704.01314","kind":"arxiv","version":3}},"canonical_sha256":"a9cacc555de26f2acd7e1342dc4c5e12b60db623d06a653407b28a6fab9bcfe4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a9cacc555de26f2acd7e1342dc4c5e12b60db623d06a653407b28a6fab9bcfe4","first_computed_at":"2026-05-18T00:35:34.159081Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:35:34.159081Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"h/RymHsI0sgYK8yXOvGIdFkV0ivt3rFMsZ5s8AncfDTw+B/OhS3DPEkxkvU4ZkHPoOWTAjJ/2nE3wOGL0/VsBA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:35:34.159601Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.01314","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5c5afaa2b918a5b70a46986c9d7b018fc49f66dc82a6d838418646eb2b4e2236","sha256:f6b8dfbbe1e137df01714325834ceb93c8d8854e0e1caa50ee348e2d598bd0cc"],"state_sha256":"7578331324477a960a102590042686ae6af2583f00921522da4deb5623d43a75"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"978Zfn2EwrIF6i2OzIBVJQG6OIkouc7WJqyJz0vSiqBIpMnw95juj8kCdhP6WULASHYizq2AZUkCE5oGjt9OBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T18:03:17.238811Z","bundle_sha256":"ef4fa3d858f95aae2f37040ecc385c7c9368a6f258939a9f2cd5a96f086ab97c"}}