{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:QD6LPVDE4IV5LQIJKH5T3DOWIQ","short_pith_number":"pith:QD6LPVDE","schema_version":"1.0","canonical_sha256":"80fcb7d464e22bd5c10951fb3d8dd6440cef2ebe71ab33dbe2f55bb9e7ba6537","source":{"kind":"arxiv","id":"2506.11485","version":1},"attestation_state":"computed","paper":{"title":"Relational Schemata in BERT Are Inducible, Not Emergent: A Study of Performance vs. Competence in Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cole Gawin","submitted_at":"2025-06-13T06:20:03Z","abstract_excerpt":"While large language models like BERT demonstrate strong empirical performance on semantic tasks, whether this reflects true conceptual competence or surface-level statistical association remains unclear. I investigate whether BERT encodes abstract relational schemata by examining internal representations of concept pairs across taxonomic, mereological, and functional relations. I compare BERT's relational classification performance with representational structure in [CLS] token embeddings. Results reveal that pretrained BERT enables high classification accuracy, indicating latent relational s"},"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":"2506.11485","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-13T06:20:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"373bfed0a692e8032ddd19f88a5a7820bdf8f096dd566075c960c15dc488b6eb","abstract_canon_sha256":"13e77e90160fe5e4ae8680fcc88394d5f04bac466cec6a2576a49e2443891fdb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:21:05.382469Z","signature_b64":"pxzAjbeDaRKpIIGzzi/X48zCrSXNTNfhk//6Cz93ZNGjmr8pGlMaYBlAmMrL+K33EwR0bAuJ1G/nW3E/BgoeAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80fcb7d464e22bd5c10951fb3d8dd6440cef2ebe71ab33dbe2f55bb9e7ba6537","last_reissued_at":"2026-07-05T11:21:05.382011Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:21:05.382011Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Relational Schemata in BERT Are Inducible, Not Emergent: A Study of Performance vs. Competence in Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Cole Gawin","submitted_at":"2025-06-13T06:20:03Z","abstract_excerpt":"While large language models like BERT demonstrate strong empirical performance on semantic tasks, whether this reflects true conceptual competence or surface-level statistical association remains unclear. I investigate whether BERT encodes abstract relational schemata by examining internal representations of concept pairs across taxonomic, mereological, and functional relations. I compare BERT's relational classification performance with representational structure in [CLS] token embeddings. Results reveal that pretrained BERT enables high classification accuracy, indicating latent relational s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.11485","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/2506.11485/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":"2506.11485","created_at":"2026-07-05T11:21:05.382069+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.11485v1","created_at":"2026-07-05T11:21:05.382069+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.11485","created_at":"2026-07-05T11:21:05.382069+00:00"},{"alias_kind":"pith_short_12","alias_value":"QD6LPVDE4IV5","created_at":"2026-07-05T11:21:05.382069+00:00"},{"alias_kind":"pith_short_16","alias_value":"QD6LPVDE4IV5LQIJ","created_at":"2026-07-05T11:21:05.382069+00:00"},{"alias_kind":"pith_short_8","alias_value":"QD6LPVDE","created_at":"2026-07-05T11:21:05.382069+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/QD6LPVDE4IV5LQIJKH5T3DOWIQ","json":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ.json","graph_json":"https://pith.science/api/pith-number/QD6LPVDE4IV5LQIJKH5T3DOWIQ/graph.json","events_json":"https://pith.science/api/pith-number/QD6LPVDE4IV5LQIJKH5T3DOWIQ/events.json","paper":"https://pith.science/paper/QD6LPVDE"},"agent_actions":{"view_html":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ","download_json":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ.json","view_paper":"https://pith.science/paper/QD6LPVDE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.11485&json=true","fetch_graph":"https://pith.science/api/pith-number/QD6LPVDE4IV5LQIJKH5T3DOWIQ/graph.json","fetch_events":"https://pith.science/api/pith-number/QD6LPVDE4IV5LQIJKH5T3DOWIQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ/action/storage_attestation","attest_author":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ/action/author_attestation","sign_citation":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ/action/citation_signature","submit_replication":"https://pith.science/pith/QD6LPVDE4IV5LQIJKH5T3DOWIQ/action/replication_record"}},"created_at":"2026-07-05T11:21:05.382069+00:00","updated_at":"2026-07-05T11:21:05.382069+00:00"}