{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:M7V5DDYXJVLTEDETKD4PCVKK2S","short_pith_number":"pith:M7V5DDYX","schema_version":"1.0","canonical_sha256":"67ebd18f174d57320c9350f8f1554ad498f980c34c1e57b13aa36a8e248ec648","source":{"kind":"arxiv","id":"2606.19638","version":1},"attestation_state":"computed","paper":{"title":"MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"David M. Smiley","submitted_at":"2026-06-17T22:31:36Z","abstract_excerpt":"Textual reuse pervades the Hebrew Bible, yet the computational methods used to detect it still rest largely on lexical overlap, and they falter once a parallel involves paraphrase, lexical substitution, or syntactic reworking. This paper introduces MiqraBERT, a Sentence-BERT model finetuned from AlephBERT (a Modern Hebrew encoder) for verse-level semantic similarity in Biblical Hebrew. The training set comprises 1,650 labeled verse and half-verse pairs: 825 true parallels drawn from the Chronicles synoptic material and from foundational studies of poetic parallelism, balanced against 825 rando"},"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":"2606.19638","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-17T22:31:36Z","cross_cats_sorted":[],"title_canon_sha256":"651ec6e71516084a1443f6e1c4f9c57dc0e09f5a502146897adad378448f1b3d","abstract_canon_sha256":"e825ab5eafe3b611b13527f122dc936cec4673d72bd815a595e15d9e65a055c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-19T16:12:30.995110Z","signature_b64":"UudBjSeqAIoYCEvnq6gUv69ueKQjWs69a87p/CT0HPkx+R925j0LOuyacJj+nYCJ/NcNWMGB7kEcaeYi6hKkCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"67ebd18f174d57320c9350f8f1554ad498f980c34c1e57b13aa36a8e248ec648","last_reissued_at":"2026-06-19T16:12:30.994768Z","signature_status":"signed_v1","first_computed_at":"2026-06-19T16:12:30.994768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"David M. Smiley","submitted_at":"2026-06-17T22:31:36Z","abstract_excerpt":"Textual reuse pervades the Hebrew Bible, yet the computational methods used to detect it still rest largely on lexical overlap, and they falter once a parallel involves paraphrase, lexical substitution, or syntactic reworking. This paper introduces MiqraBERT, a Sentence-BERT model finetuned from AlephBERT (a Modern Hebrew encoder) for verse-level semantic similarity in Biblical Hebrew. The training set comprises 1,650 labeled verse and half-verse pairs: 825 true parallels drawn from the Chronicles synoptic material and from foundational studies of poetic parallelism, balanced against 825 rando"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.19638","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/2606.19638/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":"2606.19638","created_at":"2026-06-19T16:12:30.994830+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.19638v1","created_at":"2026-06-19T16:12:30.994830+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.19638","created_at":"2026-06-19T16:12:30.994830+00:00"},{"alias_kind":"pith_short_12","alias_value":"M7V5DDYXJVLT","created_at":"2026-06-19T16:12:30.994830+00:00"},{"alias_kind":"pith_short_16","alias_value":"M7V5DDYXJVLTEDET","created_at":"2026-06-19T16:12:30.994830+00:00"},{"alias_kind":"pith_short_8","alias_value":"M7V5DDYX","created_at":"2026-06-19T16:12:30.994830+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/M7V5DDYXJVLTEDETKD4PCVKK2S","json":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S.json","graph_json":"https://pith.science/api/pith-number/M7V5DDYXJVLTEDETKD4PCVKK2S/graph.json","events_json":"https://pith.science/api/pith-number/M7V5DDYXJVLTEDETKD4PCVKK2S/events.json","paper":"https://pith.science/paper/M7V5DDYX"},"agent_actions":{"view_html":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S","download_json":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S.json","view_paper":"https://pith.science/paper/M7V5DDYX","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.19638&json=true","fetch_graph":"https://pith.science/api/pith-number/M7V5DDYXJVLTEDETKD4PCVKK2S/graph.json","fetch_events":"https://pith.science/api/pith-number/M7V5DDYXJVLTEDETKD4PCVKK2S/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S/action/timestamp_anchor","attest_storage":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S/action/storage_attestation","attest_author":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S/action/author_attestation","sign_citation":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S/action/citation_signature","submit_replication":"https://pith.science/pith/M7V5DDYXJVLTEDETKD4PCVKK2S/action/replication_record"}},"created_at":"2026-06-19T16:12:30.994830+00:00","updated_at":"2026-06-19T16:12:30.994830+00:00"}