{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:WWLYGNZCRNBWT3TQ3FLD2KOR5G","short_pith_number":"pith:WWLYGNZC","canonical_record":{"source":{"id":"1804.06610","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-18T09:07:16Z","cross_cats_sorted":[],"title_canon_sha256":"329e874d745d35c3727833fc9188d3e5d51083b7a3f42a0eb8d048d77a5e8987","abstract_canon_sha256":"27243f1ce5f8e443bcc4dbc11480d9e2ffdf3ecf85ce18a5fd600efb816ce450"},"schema_version":"1.0"},"canonical_sha256":"b5978337228b4369ee70d9563d29d1e9a34137cad70046fc6a70eeaeec9994ab","source":{"kind":"arxiv","id":"1804.06610","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.06610","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"arxiv_version","alias_value":"1804.06610v3","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.06610","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"pith_short_12","alias_value":"WWLYGNZCRNBW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWLYGNZCRNBWT3TQ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWLYGNZC","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:WWLYGNZCRNBWT3TQ3FLD2KOR5G","target":"record","payload":{"canonical_record":{"source":{"id":"1804.06610","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-18T09:07:16Z","cross_cats_sorted":[],"title_canon_sha256":"329e874d745d35c3727833fc9188d3e5d51083b7a3f42a0eb8d048d77a5e8987","abstract_canon_sha256":"27243f1ce5f8e443bcc4dbc11480d9e2ffdf3ecf85ce18a5fd600efb816ce450"},"schema_version":"1.0"},"canonical_sha256":"b5978337228b4369ee70d9563d29d1e9a34137cad70046fc6a70eeaeec9994ab","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:17:16.314401Z","signature_b64":"NOe8WLeRE2iQSLam8Paiwpy6kRwURjSdlDL4X5vcFX40SDSHgMRMFPAmzRal09lFwQrn9w6QaxyMTJHrDuA7CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b5978337228b4369ee70d9563d29d1e9a34137cad70046fc6a70eeaeec9994ab","last_reissued_at":"2026-05-18T00:17:16.313732Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:17:16.313732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1804.06610","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":"2026-05-18T00:17:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"srupB9iufnm9TJUs1Y9h60QmWuGITelEfzuMwlzril4NpdzRb871mjRDXBXbSe9E0lFTteC3MWscHFXrz8iAAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T22:39:47.616231Z"},"content_sha256":"61f53dbadb87b4dc33c72cf4b7536cb68d54ec30a69fc2423b69fc03be9f336a","schema_version":"1.0","event_id":"sha256:61f53dbadb87b4dc33c72cf4b7536cb68d54ec30a69fc2423b69fc03be9f336a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:WWLYGNZCRNBWT3TQ3FLD2KOR5G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"End-to-end Graph-based TAG Parsing with Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jungo Kasai, Owen Rambow, Pauli Xu, Robert Frank, William Merrill","submitted_at":"2018-04-18T09:07:16Z","abstract_excerpt":"We present a graph-based Tree Adjoining Grammar (TAG) parser that uses BiLSTMs, highway connections, and character-level CNNs. Our best end-to-end parser, which jointly performs supertagging, POS tagging, and parsing, outperforms the previously reported best results by more than 2.2 LAS and UAS points. The graph-based parsing architecture allows for global inference and rich feature representations for TAG parsing, alleviating the fundamental trade-off between transition-based and graph-based parsing systems. We also demonstrate that the proposed parser achieves state-of-the-art performance in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.06610","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":"2026-05-18T00:17:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mnZhqRcXHp1kzrHvkUwajWkK8B9rRkP28uEthjFsnTTZwYM2WCxDFjerkW0pssyUdCcEZGgC0n8YK+OMLz2lAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T22:39:47.616864Z"},"content_sha256":"a6d31c8b4e909ce36345a86574cb36259c04b98be9a35fa47ccf02e772eb15c5","schema_version":"1.0","event_id":"sha256:a6d31c8b4e909ce36345a86574cb36259c04b98be9a35fa47ccf02e772eb15c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/bundle.json","state_url":"https://pith.science/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/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":"2026-05-28T22:39:47Z","links":{"resolver":"https://pith.science/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G","bundle":"https://pith.science/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/bundle.json","state":"https://pith.science/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WWLYGNZCRNBWT3TQ3FLD2KOR5G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:WWLYGNZCRNBWT3TQ3FLD2KOR5G","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":"27243f1ce5f8e443bcc4dbc11480d9e2ffdf3ecf85ce18a5fd600efb816ce450","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-18T09:07:16Z","title_canon_sha256":"329e874d745d35c3727833fc9188d3e5d51083b7a3f42a0eb8d048d77a5e8987"},"schema_version":"1.0","source":{"id":"1804.06610","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1804.06610","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"arxiv_version","alias_value":"1804.06610v3","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.06610","created_at":"2026-05-18T00:17:16Z"},{"alias_kind":"pith_short_12","alias_value":"WWLYGNZCRNBW","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"WWLYGNZCRNBWT3TQ","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"WWLYGNZC","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:a6d31c8b4e909ce36345a86574cb36259c04b98be9a35fa47ccf02e772eb15c5","target":"graph","created_at":"2026-05-18T00:17:16Z","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 graph-based Tree Adjoining Grammar (TAG) parser that uses BiLSTMs, highway connections, and character-level CNNs. Our best end-to-end parser, which jointly performs supertagging, POS tagging, and parsing, outperforms the previously reported best results by more than 2.2 LAS and UAS points. The graph-based parsing architecture allows for global inference and rich feature representations for TAG parsing, alleviating the fundamental trade-off between transition-based and graph-based parsing systems. We also demonstrate that the proposed parser achieves state-of-the-art performance in","authors_text":"Jungo Kasai, Owen Rambow, Pauli Xu, Robert Frank, William Merrill","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-18T09:07:16Z","title":"End-to-end Graph-based TAG Parsing with Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.06610","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":"sha256:61f53dbadb87b4dc33c72cf4b7536cb68d54ec30a69fc2423b69fc03be9f336a","target":"record","created_at":"2026-05-18T00:17:16Z","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":"27243f1ce5f8e443bcc4dbc11480d9e2ffdf3ecf85ce18a5fd600efb816ce450","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-04-18T09:07:16Z","title_canon_sha256":"329e874d745d35c3727833fc9188d3e5d51083b7a3f42a0eb8d048d77a5e8987"},"schema_version":"1.0","source":{"id":"1804.06610","kind":"arxiv","version":3}},"canonical_sha256":"b5978337228b4369ee70d9563d29d1e9a34137cad70046fc6a70eeaeec9994ab","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b5978337228b4369ee70d9563d29d1e9a34137cad70046fc6a70eeaeec9994ab","first_computed_at":"2026-05-18T00:17:16.313732Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:17:16.313732Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NOe8WLeRE2iQSLam8Paiwpy6kRwURjSdlDL4X5vcFX40SDSHgMRMFPAmzRal09lFwQrn9w6QaxyMTJHrDuA7CA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:17:16.314401Z","signed_message":"canonical_sha256_bytes"},"source_id":"1804.06610","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61f53dbadb87b4dc33c72cf4b7536cb68d54ec30a69fc2423b69fc03be9f336a","sha256:a6d31c8b4e909ce36345a86574cb36259c04b98be9a35fa47ccf02e772eb15c5"],"state_sha256":"7b4e6edc480ee89cbb3bd90494447e2d3ab58293c5dc3f90bb00ae5b9c510780"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WPTQt1Q6OevOPzr5COSJPzJ7qOe9/HDPgijbg9/6mzlsISJpUqd2iXniMag03KBbeHWN2xENiHqAwiT5+2QrAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T22:39:47.620098Z","bundle_sha256":"dbaae02749eb05b3e00a6c1451542ac7d75223343a81fb5629d204dddbfc8847"}}