{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GEKXONJS2CVJNDPLQH3WKFKTLQ","short_pith_number":"pith:GEKXONJS","canonical_record":{"source":{"id":"2509.01147","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-01T05:49:49Z","cross_cats_sorted":[],"title_canon_sha256":"12eb74cd7196a6e0ae0e7a4759747bea1add1485bd14ce8307901199a1db4561","abstract_canon_sha256":"24ada9dc3a1b5245a0091153777b006a0a3f08f6e874431002b0044d699ced0c"},"schema_version":"1.0"},"canonical_sha256":"3115773532d0aa968deb81f76515535c16e7bad724160dec25d4e7b84d19bbff","source":{"kind":"arxiv","id":"2509.01147","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.01147","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"arxiv_version","alias_value":"2509.01147v1","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.01147","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_12","alias_value":"GEKXONJS2CVJ","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_16","alias_value":"GEKXONJS2CVJNDPL","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_8","alias_value":"GEKXONJS","created_at":"2026-07-05T12:02:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GEKXONJS2CVJNDPLQH3WKFKTLQ","target":"record","payload":{"canonical_record":{"source":{"id":"2509.01147","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-01T05:49:49Z","cross_cats_sorted":[],"title_canon_sha256":"12eb74cd7196a6e0ae0e7a4759747bea1add1485bd14ce8307901199a1db4561","abstract_canon_sha256":"24ada9dc3a1b5245a0091153777b006a0a3f08f6e874431002b0044d699ced0c"},"schema_version":"1.0"},"canonical_sha256":"3115773532d0aa968deb81f76515535c16e7bad724160dec25d4e7b84d19bbff","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:02:54.835814Z","signature_b64":"Kpy1+yVIGW4NJnOCJyG+lPF0F5pMejSvLnsySRgcvjOMKgwn5qRDl9FMtAOVEc6gXK5ejhHy+psSYjTWFEM2CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3115773532d0aa968deb81f76515535c16e7bad724160dec25d4e7b84d19bbff","last_reissued_at":"2026-07-05T12:02:54.835298Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:02:54.835298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.01147","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":"2026-07-05T12:02:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uGEFdGwcp3Zyc9t4uYRs8KvPK1h2BmJ6yu/HUejrPj41lAsh8m5/3azGqhhqqfQrhPSovn7/uXbBoO3L+yAnDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:41:07.361978Z"},"content_sha256":"897c60479494bd06fb82d187e8ac769931d70c7ecbe09e01bb0f5e81fe7d9dd2","schema_version":"1.0","event_id":"sha256:897c60479494bd06fb82d187e8ac769931d70c7ecbe09e01bb0f5e81fe7d9dd2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GEKXONJS2CVJNDPLQH3WKFKTLQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Zero-shot Cross-lingual NER via Mitigating Language Difference: An Entity-aligned Translation Perspective","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dong Zhang, Guodong Zhou, Shoushan Li, Sophia Yat Mei Lee, Zhihao Zhang","submitted_at":"2025-09-01T05:49:49Z","abstract_excerpt":"Cross-lingual Named Entity Recognition (CL-NER) aims to transfer knowledge from high-resource languages to low-resource languages. However, existing zero-shot CL-NER (ZCL-NER) approaches primarily focus on Latin script language (LSL), where shared linguistic features facilitate effective knowledge transfer. In contrast, for non-Latin script language (NSL), such as Chinese and Japanese, performance often degrades due to deep structural differences. To address these challenges, we propose an entity-aligned translation (EAT) approach. Leveraging large language models (LLMs), EAT employs a dual-tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.01147","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/2509.01147/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":"2026-07-05T12:02:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/JSqivCYgOLd862NOo92QNsMD0D3cbGiTlBNiWhioQs+u7pyiZCVeoJcj1O9PRfxAmfMl25almuf3jSA+poSCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:41:07.362518Z"},"content_sha256":"6c69a6c7930d9a5f9e3e88d0ab12f15e80e4542a6611c810a57cf183c8b00778","schema_version":"1.0","event_id":"sha256:6c69a6c7930d9a5f9e3e88d0ab12f15e80e4542a6611c810a57cf183c8b00778"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/bundle.json","state_url":"https://pith.science/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/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":"2026-08-08T20:41:07Z","links":{"resolver":"https://pith.science/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ","bundle":"https://pith.science/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/bundle.json","state":"https://pith.science/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GEKXONJS2CVJNDPLQH3WKFKTLQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GEKXONJS2CVJNDPLQH3WKFKTLQ","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":"24ada9dc3a1b5245a0091153777b006a0a3f08f6e874431002b0044d699ced0c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-01T05:49:49Z","title_canon_sha256":"12eb74cd7196a6e0ae0e7a4759747bea1add1485bd14ce8307901199a1db4561"},"schema_version":"1.0","source":{"id":"2509.01147","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.01147","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"arxiv_version","alias_value":"2509.01147v1","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.01147","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_12","alias_value":"GEKXONJS2CVJ","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_16","alias_value":"GEKXONJS2CVJNDPL","created_at":"2026-07-05T12:02:54Z"},{"alias_kind":"pith_short_8","alias_value":"GEKXONJS","created_at":"2026-07-05T12:02:54Z"}],"graph_snapshots":[{"event_id":"sha256:6c69a6c7930d9a5f9e3e88d0ab12f15e80e4542a6611c810a57cf183c8b00778","target":"graph","created_at":"2026-07-05T12:02:54Z","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/2509.01147/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cross-lingual Named Entity Recognition (CL-NER) aims to transfer knowledge from high-resource languages to low-resource languages. However, existing zero-shot CL-NER (ZCL-NER) approaches primarily focus on Latin script language (LSL), where shared linguistic features facilitate effective knowledge transfer. In contrast, for non-Latin script language (NSL), such as Chinese and Japanese, performance often degrades due to deep structural differences. To address these challenges, we propose an entity-aligned translation (EAT) approach. Leveraging large language models (LLMs), EAT employs a dual-tr","authors_text":"Dong Zhang, Guodong Zhou, Shoushan Li, Sophia Yat Mei Lee, Zhihao Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-01T05:49:49Z","title":"Zero-shot Cross-lingual NER via Mitigating Language Difference: An Entity-aligned Translation Perspective"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.01147","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":"sha256:897c60479494bd06fb82d187e8ac769931d70c7ecbe09e01bb0f5e81fe7d9dd2","target":"record","created_at":"2026-07-05T12:02:54Z","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":"24ada9dc3a1b5245a0091153777b006a0a3f08f6e874431002b0044d699ced0c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2025-09-01T05:49:49Z","title_canon_sha256":"12eb74cd7196a6e0ae0e7a4759747bea1add1485bd14ce8307901199a1db4561"},"schema_version":"1.0","source":{"id":"2509.01147","kind":"arxiv","version":1}},"canonical_sha256":"3115773532d0aa968deb81f76515535c16e7bad724160dec25d4e7b84d19bbff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3115773532d0aa968deb81f76515535c16e7bad724160dec25d4e7b84d19bbff","first_computed_at":"2026-07-05T12:02:54.835298Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:02:54.835298Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kpy1+yVIGW4NJnOCJyG+lPF0F5pMejSvLnsySRgcvjOMKgwn5qRDl9FMtAOVEc6gXK5ejhHy+psSYjTWFEM2CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:02:54.835814Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.01147","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:897c60479494bd06fb82d187e8ac769931d70c7ecbe09e01bb0f5e81fe7d9dd2","sha256:6c69a6c7930d9a5f9e3e88d0ab12f15e80e4542a6611c810a57cf183c8b00778"],"state_sha256":"1689b551711798e782fc638e1e6ee2cf11e547027a822b945912f4e28858b15e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d3EThVcf2j3OCQ1DKdIRj9BHEdqKdhjnV2CFhdR6/PIGAQi01nHn20MtIA7S1TUWUxvgTisbJi/g1I1KHE3kDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:41:07.366270Z","bundle_sha256":"f3889a26da77bf028fc775da097d0ae06056ac49db7236065a0c15d4c086d3e6"}}