{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:YRYETUSQTZV4JOIRNXR44ZV2VA","short_pith_number":"pith:YRYETUSQ","schema_version":"1.0","canonical_sha256":"c47049d2509e6bc4b9116de3ce66baa82f8d45b433b51fabb3d6dc6a3957430f","source":{"kind":"arxiv","id":"2205.13351","version":1},"attestation_state":"computed","paper":{"title":"LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Arian Askari, Gabriella Pasi, Georgios Peikos, Suzan Verberne","submitted_at":"2022-05-26T13:32:33Z","abstract_excerpt":"This paper summarizes our approaches submitted to the case law retrieval task in the Competition on Legal Information Extraction/Entailment (COLIEE) 2022. Our methodology consists of four steps; in detail, given a legal case as a query, we reformulate it by extracting various meaningful sentences or n-grams. Then, we utilize the pre-processed query case to retrieve an initial set of possible relevant legal cases, which we further re-rank. Lastly, we aggregate the relevance scores obtained by the first stage and the re-ranking models to improve retrieval effectiveness. In each step of our metho"},"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":"2205.13351","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.IR","submitted_at":"2022-05-26T13:32:33Z","cross_cats_sorted":[],"title_canon_sha256":"3472d30b21969f8abb50aafbe67730c4ff5523b12f2524b352e222a6cbb38570","abstract_canon_sha256":"8f34532a078955a498a8e45987f1475dd72938188159bed54b1d45aeeb9d070e"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:26:42.296677Z","signature_b64":"nP2zF4MDkYgCTFS72JNcezfj+o8pZdJry0URYN/3sQfXXHKC2lf0eFmR+rJewiuu8Q6BfM/GO7pzxxWZ0PUnAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c47049d2509e6bc4b9116de3ce66baa82f8d45b433b51fabb3d6dc6a3957430f","last_reissued_at":"2026-07-05T04:26:42.296198Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:26:42.296198Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"LeiBi@COLIEE 2022: Aggregating Tuned Lexical Models with a Cluster-driven BERT-based Model for Case Law Retrieval","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.IR","authors_text":"Arian Askari, Gabriella Pasi, Georgios Peikos, Suzan Verberne","submitted_at":"2022-05-26T13:32:33Z","abstract_excerpt":"This paper summarizes our approaches submitted to the case law retrieval task in the Competition on Legal Information Extraction/Entailment (COLIEE) 2022. Our methodology consists of four steps; in detail, given a legal case as a query, we reformulate it by extracting various meaningful sentences or n-grams. Then, we utilize the pre-processed query case to retrieve an initial set of possible relevant legal cases, which we further re-rank. Lastly, we aggregate the relevance scores obtained by the first stage and the re-ranking models to improve retrieval effectiveness. In each step of our metho"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.13351","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/2205.13351/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":"2205.13351","created_at":"2026-07-05T04:26:42.296280+00:00"},{"alias_kind":"arxiv_version","alias_value":"2205.13351v1","created_at":"2026-07-05T04:26:42.296280+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.13351","created_at":"2026-07-05T04:26:42.296280+00:00"},{"alias_kind":"pith_short_12","alias_value":"YRYETUSQTZV4","created_at":"2026-07-05T04:26:42.296280+00:00"},{"alias_kind":"pith_short_16","alias_value":"YRYETUSQTZV4JOIR","created_at":"2026-07-05T04:26:42.296280+00:00"},{"alias_kind":"pith_short_8","alias_value":"YRYETUSQ","created_at":"2026-07-05T04:26:42.296280+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/YRYETUSQTZV4JOIRNXR44ZV2VA","json":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA.json","graph_json":"https://pith.science/api/pith-number/YRYETUSQTZV4JOIRNXR44ZV2VA/graph.json","events_json":"https://pith.science/api/pith-number/YRYETUSQTZV4JOIRNXR44ZV2VA/events.json","paper":"https://pith.science/paper/YRYETUSQ"},"agent_actions":{"view_html":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA","download_json":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA.json","view_paper":"https://pith.science/paper/YRYETUSQ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2205.13351&json=true","fetch_graph":"https://pith.science/api/pith-number/YRYETUSQTZV4JOIRNXR44ZV2VA/graph.json","fetch_events":"https://pith.science/api/pith-number/YRYETUSQTZV4JOIRNXR44ZV2VA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA/action/storage_attestation","attest_author":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA/action/author_attestation","sign_citation":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA/action/citation_signature","submit_replication":"https://pith.science/pith/YRYETUSQTZV4JOIRNXR44ZV2VA/action/replication_record"}},"created_at":"2026-07-05T04:26:42.296280+00:00","updated_at":"2026-07-05T04:26:42.296280+00:00"}