{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:62CF3EREYSPMS7YYLT7BWBLROB","short_pith_number":"pith:62CF3ERE","schema_version":"1.0","canonical_sha256":"f6845d9224c49ec97f185cfe1b05717045977fd883006f9f78903a28a1dac065","source":{"kind":"arxiv","id":"2106.04559","version":1},"attestation_state":"computed","paper":{"title":"Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"\\'Akos K\\'ad\\'ar, Hamidreza Shahidi, Harsh Barot, Jawad Ateeq, Keyi Tang, Meidan Alon, Peng Xu, Wei Yang, Wenjie Zi, Yanshuai Cao","submitted_at":"2021-06-08T17:46:20Z","abstract_excerpt":"A natural language database interface (NLDB) can democratize data-driven insights for non-technical users. However, existing Text-to-SQL semantic parsers cannot achieve high enough accuracy in the cross-database setting to allow good usability in practice. This work presents Turing, a NLDB system toward bridging this gap. The cross-domain semantic parser of Turing with our novel value prediction method achieves $75.1\\%$ execution accuracy, and $78.3\\%$ top-5 beam execution accuracy on the Spider validation set. To benefit from the higher beam accuracy, we design an interactive system where the"},"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":"2106.04559","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2021-06-08T17:46:20Z","cross_cats_sorted":[],"title_canon_sha256":"1166af4f63b79c3cf020155aa327b8aa96b42f1796b0a0fc81a7e5389450ae4e","abstract_canon_sha256":"c84fdcf0b126caec479eec3e25f89eb3aac09732924edead7c7fe0b85fed77b0"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:47:16.620791Z","signature_b64":"DgdVjb+DYRrsuxTls5IXoeR4iOFqT8hsiG6cmRZzVC6KYoP6tQww4GkIMYbG9TKcfUKE0+oFpqUoorM62oAgBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f6845d9224c49ec97f185cfe1b05717045977fd883006f9f78903a28a1dac065","last_reissued_at":"2026-07-05T02:47:16.620276Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:47:16.620276Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"\\'Akos K\\'ad\\'ar, Hamidreza Shahidi, Harsh Barot, Jawad Ateeq, Keyi Tang, Meidan Alon, Peng Xu, Wei Yang, Wenjie Zi, Yanshuai Cao","submitted_at":"2021-06-08T17:46:20Z","abstract_excerpt":"A natural language database interface (NLDB) can democratize data-driven insights for non-technical users. However, existing Text-to-SQL semantic parsers cannot achieve high enough accuracy in the cross-database setting to allow good usability in practice. This work presents Turing, a NLDB system toward bridging this gap. The cross-domain semantic parser of Turing with our novel value prediction method achieves $75.1\\%$ execution accuracy, and $78.3\\%$ top-5 beam execution accuracy on the Spider validation set. To benefit from the higher beam accuracy, we design an interactive system where the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.04559","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/2106.04559/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":"2106.04559","created_at":"2026-07-05T02:47:16.620336+00:00"},{"alias_kind":"arxiv_version","alias_value":"2106.04559v1","created_at":"2026-07-05T02:47:16.620336+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.04559","created_at":"2026-07-05T02:47:16.620336+00:00"},{"alias_kind":"pith_short_12","alias_value":"62CF3EREYSPM","created_at":"2026-07-05T02:47:16.620336+00:00"},{"alias_kind":"pith_short_16","alias_value":"62CF3EREYSPMS7YY","created_at":"2026-07-05T02:47:16.620336+00:00"},{"alias_kind":"pith_short_8","alias_value":"62CF3ERE","created_at":"2026-07-05T02:47:16.620336+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/62CF3EREYSPMS7YYLT7BWBLROB","json":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB.json","graph_json":"https://pith.science/api/pith-number/62CF3EREYSPMS7YYLT7BWBLROB/graph.json","events_json":"https://pith.science/api/pith-number/62CF3EREYSPMS7YYLT7BWBLROB/events.json","paper":"https://pith.science/paper/62CF3ERE"},"agent_actions":{"view_html":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB","download_json":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB.json","view_paper":"https://pith.science/paper/62CF3ERE","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2106.04559&json=true","fetch_graph":"https://pith.science/api/pith-number/62CF3EREYSPMS7YYLT7BWBLROB/graph.json","fetch_events":"https://pith.science/api/pith-number/62CF3EREYSPMS7YYLT7BWBLROB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB/action/storage_attestation","attest_author":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB/action/author_attestation","sign_citation":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB/action/citation_signature","submit_replication":"https://pith.science/pith/62CF3EREYSPMS7YYLT7BWBLROB/action/replication_record"}},"created_at":"2026-07-05T02:47:16.620336+00:00","updated_at":"2026-07-05T02:47:16.620336+00:00"}