{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:VQQH2KBQCA7IVUV7IVFAPQRPXN","short_pith_number":"pith:VQQH2KBQ","schema_version":"1.0","canonical_sha256":"ac207d2830103e8ad2bf454a07c22fbb59eedc7e2a0d335c5f2f952688ba793f","source":{"kind":"arxiv","id":"2505.03473","version":1},"attestation_state":"computed","paper":{"title":"Evaluation of LLMs on Long-tail Entity Linking in Historical Documents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Beatrice Fiuman\\`o, Emanuele Lenzi, Leonardo Piano, Lia Draetta, Luana Bulla, Marta Boscariol","submitted_at":"2025-05-06T12:25:15Z","abstract_excerpt":"Entity Linking (EL) plays a crucial role in Natural Language Processing (NLP) applications, enabling the disambiguation of entity mentions by linking them to their corresponding entries in a reference knowledge base (KB). Thanks to their deep contextual understanding capabilities, LLMs offer a new perspective to tackle EL, promising better results than traditional methods. Despite the impressive generalization capabilities of LLMs, linking less popular, long-tail entities remains challenging as these entities are often underrepresented in training data and knowledge bases. Furthermore, the lon"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.03473","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-06T12:25:15Z","cross_cats_sorted":[],"title_canon_sha256":"2a24f4592a403e9ed096f7b45b5c404868d1274c7161252df3c72b21faa66d22","abstract_canon_sha256":"80544249ac85b690d7276df183f2171e5f49e5721463dacdb3b45c89a849ced9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:59:16.751953Z","signature_b64":"tBnFq134b/P52frL33bjkb9ijarIM7DXuSPaabwBbqyHZogA+IE7CumPWcoyy65Ry6VpMm5ocr0UJR/PY/SKDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac207d2830103e8ad2bf454a07c22fbb59eedc7e2a0d335c5f2f952688ba793f","last_reissued_at":"2026-07-05T10:59:16.751493Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:59:16.751493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Evaluation of LLMs on Long-tail Entity Linking in Historical Documents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Beatrice Fiuman\\`o, Emanuele Lenzi, Leonardo Piano, Lia Draetta, Luana Bulla, Marta Boscariol","submitted_at":"2025-05-06T12:25:15Z","abstract_excerpt":"Entity Linking (EL) plays a crucial role in Natural Language Processing (NLP) applications, enabling the disambiguation of entity mentions by linking them to their corresponding entries in a reference knowledge base (KB). Thanks to their deep contextual understanding capabilities, LLMs offer a new perspective to tackle EL, promising better results than traditional methods. Despite the impressive generalization capabilities of LLMs, linking less popular, long-tail entities remains challenging as these entities are often underrepresented in training data and knowledge bases. Furthermore, the lon"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03473","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/2505.03473/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.03473","created_at":"2026-07-05T10:59:16.751550+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.03473v1","created_at":"2026-07-05T10:59:16.751550+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03473","created_at":"2026-07-05T10:59:16.751550+00:00"},{"alias_kind":"pith_short_12","alias_value":"VQQH2KBQCA7I","created_at":"2026-07-05T10:59:16.751550+00:00"},{"alias_kind":"pith_short_16","alias_value":"VQQH2KBQCA7IVUV7","created_at":"2026-07-05T10:59:16.751550+00:00"},{"alias_kind":"pith_short_8","alias_value":"VQQH2KBQ","created_at":"2026-07-05T10:59:16.751550+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN","json":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN.json","graph_json":"https://pith.science/api/pith-number/VQQH2KBQCA7IVUV7IVFAPQRPXN/graph.json","events_json":"https://pith.science/api/pith-number/VQQH2KBQCA7IVUV7IVFAPQRPXN/events.json","paper":"https://pith.science/paper/VQQH2KBQ"},"agent_actions":{"view_html":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN","download_json":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN.json","view_paper":"https://pith.science/paper/VQQH2KBQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.03473&json=true","fetch_graph":"https://pith.science/api/pith-number/VQQH2KBQCA7IVUV7IVFAPQRPXN/graph.json","fetch_events":"https://pith.science/api/pith-number/VQQH2KBQCA7IVUV7IVFAPQRPXN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN/action/storage_attestation","attest_author":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN/action/author_attestation","sign_citation":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN/action/citation_signature","submit_replication":"https://pith.science/pith/VQQH2KBQCA7IVUV7IVFAPQRPXN/action/replication_record"}},"created_at":"2026-07-05T10:59:16.751550+00:00","updated_at":"2026-07-05T10:59:16.751550+00:00"}