{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:OEO52PY2UMZCCFW67IQN2YDTH3","short_pith_number":"pith:OEO52PY2","schema_version":"1.0","canonical_sha256":"711ddd3f1aa3322116defa20dd60733ed97eb0572512b596384c54410be197bb","source":{"kind":"arxiv","id":"2507.22419","version":1},"attestation_state":"computed","paper":{"title":"Systematic Evaluation of Knowledge Graph Repair with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.DB","authors_text":"Alberto Sangiovanni-Vinentelli, Gabe Fierro, Han Li, Pierluigi Nuzzo, Tianzhen Hong, Tung-Wei Lin","submitted_at":"2025-07-30T06:46:30Z","abstract_excerpt":"We present a systematic approach for evaluating the quality of knowledge graph repairs with respect to constraint violations defined in shapes constraint language (SHACL). Current evaluation methods rely on \\emph{ad hoc} datasets, which limits the rigorous analysis of repair systems in more general settings. Our method addresses this gap by systematically generating violations using a novel mechanism, termed violation-inducing operations (VIOs). We use the proposed evaluation framework to assess a range of repair systems which we build using large language models. We analyze the performance of"},"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":"2507.22419","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DB","submitted_at":"2025-07-30T06:46:30Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"97e586a77be1394d24dd88d655d7c852bee0dc83ed0ed58ff57bbd3f44ad1ecb","abstract_canon_sha256":"a86eedd3b87525ec420d21455f0088ffa7bb8b72df6d6df113195a10c36a5e5a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:41.684943Z","signature_b64":"ENGKMQ1scTIljgpbHXZLunBGQU9xlgjWrihcl/4aK0Udpubxhzll8+keHjfRDHn8wQU6UeXskeQM87mDMs90CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"711ddd3f1aa3322116defa20dd60733ed97eb0572512b596384c54410be197bb","last_reissued_at":"2026-07-05T11:45:41.684483Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:41.684483Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Systematic Evaluation of Knowledge Graph Repair with Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.DB","authors_text":"Alberto Sangiovanni-Vinentelli, Gabe Fierro, Han Li, Pierluigi Nuzzo, Tianzhen Hong, Tung-Wei Lin","submitted_at":"2025-07-30T06:46:30Z","abstract_excerpt":"We present a systematic approach for evaluating the quality of knowledge graph repairs with respect to constraint violations defined in shapes constraint language (SHACL). Current evaluation methods rely on \\emph{ad hoc} datasets, which limits the rigorous analysis of repair systems in more general settings. Our method addresses this gap by systematically generating violations using a novel mechanism, termed violation-inducing operations (VIOs). We use the proposed evaluation framework to assess a range of repair systems which we build using large language models. We analyze the performance of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.22419","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/2507.22419/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":"2507.22419","created_at":"2026-07-05T11:45:41.684541+00:00"},{"alias_kind":"arxiv_version","alias_value":"2507.22419v1","created_at":"2026-07-05T11:45:41.684541+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.22419","created_at":"2026-07-05T11:45:41.684541+00:00"},{"alias_kind":"pith_short_12","alias_value":"OEO52PY2UMZC","created_at":"2026-07-05T11:45:41.684541+00:00"},{"alias_kind":"pith_short_16","alias_value":"OEO52PY2UMZCCFW6","created_at":"2026-07-05T11:45:41.684541+00:00"},{"alias_kind":"pith_short_8","alias_value":"OEO52PY2","created_at":"2026-07-05T11:45:41.684541+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/OEO52PY2UMZCCFW67IQN2YDTH3","json":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3.json","graph_json":"https://pith.science/api/pith-number/OEO52PY2UMZCCFW67IQN2YDTH3/graph.json","events_json":"https://pith.science/api/pith-number/OEO52PY2UMZCCFW67IQN2YDTH3/events.json","paper":"https://pith.science/paper/OEO52PY2"},"agent_actions":{"view_html":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3","download_json":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3.json","view_paper":"https://pith.science/paper/OEO52PY2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2507.22419&json=true","fetch_graph":"https://pith.science/api/pith-number/OEO52PY2UMZCCFW67IQN2YDTH3/graph.json","fetch_events":"https://pith.science/api/pith-number/OEO52PY2UMZCCFW67IQN2YDTH3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3/action/storage_attestation","attest_author":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3/action/author_attestation","sign_citation":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3/action/citation_signature","submit_replication":"https://pith.science/pith/OEO52PY2UMZCCFW67IQN2YDTH3/action/replication_record"}},"created_at":"2026-07-05T11:45:41.684541+00:00","updated_at":"2026-07-05T11:45:41.684541+00:00"}