{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:WTSLSGQIPCGCCR46QFSFPLERWX","short_pith_number":"pith:WTSLSGQI","schema_version":"1.0","canonical_sha256":"b4e4b91a08788c21479e816457ac91b5d2b021ad8217a5512ff7628dc14e4a0a","source":{"kind":"arxiv","id":"2210.12217","version":1},"attestation_state":"computed","paper":{"title":"Entailer: Answering Questions with Faithful and Truthful Chains of Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Bhavana Dalvi Mishra, Oyvind Tafjord, Peter Clark","submitted_at":"2022-10-21T19:51:56Z","abstract_excerpt":"Our goal is a question-answering (QA) system that can show how its answers are implied by its own internal beliefs via a systematic chain of reasoning. Such a capability would allow better understanding of why a model produced the answer it did. Our approach is to recursively combine a trained backward-chaining model, capable of generating a set of premises entailing an answer hypothesis, with a verifier that checks that the model itself believes those premises (and the entailment itself) through self-querying. To our knowledge, this is the first system to generate multistep chains that are bo"},"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":"2210.12217","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2022-10-21T19:51:56Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"ddc70d7099e301b592d7c6d7ed663e47999c0f11a3a0fd8f7fa8838e09363e52","abstract_canon_sha256":"a84c90b1a36e7f0d5a5b4513f19d97288bd85d2c9352c94d2fc4edfe91220dac"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:09:25.246812Z","signature_b64":"A6p6ma9yZcHtzVHzateg8wkUQXXUe6RVdlvgi0fGjQijiCX814ur3QSQf5VgxNs91gXdPRqZJOJPImahb/SGAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b4e4b91a08788c21479e816457ac91b5d2b021ad8217a5512ff7628dc14e4a0a","last_reissued_at":"2026-07-05T05:09:25.246270Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:09:25.246270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Entailer: Answering Questions with Faithful and Truthful Chains of Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Bhavana Dalvi Mishra, Oyvind Tafjord, Peter Clark","submitted_at":"2022-10-21T19:51:56Z","abstract_excerpt":"Our goal is a question-answering (QA) system that can show how its answers are implied by its own internal beliefs via a systematic chain of reasoning. Such a capability would allow better understanding of why a model produced the answer it did. Our approach is to recursively combine a trained backward-chaining model, capable of generating a set of premises entailing an answer hypothesis, with a verifier that checks that the model itself believes those premises (and the entailment itself) through self-querying. To our knowledge, this is the first system to generate multistep chains that are bo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.12217","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/2210.12217/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":"2210.12217","created_at":"2026-07-05T05:09:25.246335+00:00"},{"alias_kind":"arxiv_version","alias_value":"2210.12217v1","created_at":"2026-07-05T05:09:25.246335+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.12217","created_at":"2026-07-05T05:09:25.246335+00:00"},{"alias_kind":"pith_short_12","alias_value":"WTSLSGQIPCGC","created_at":"2026-07-05T05:09:25.246335+00:00"},{"alias_kind":"pith_short_16","alias_value":"WTSLSGQIPCGCCR46","created_at":"2026-07-05T05:09:25.246335+00:00"},{"alias_kind":"pith_short_8","alias_value":"WTSLSGQI","created_at":"2026-07-05T05:09:25.246335+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/WTSLSGQIPCGCCR46QFSFPLERWX","json":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX.json","graph_json":"https://pith.science/api/pith-number/WTSLSGQIPCGCCR46QFSFPLERWX/graph.json","events_json":"https://pith.science/api/pith-number/WTSLSGQIPCGCCR46QFSFPLERWX/events.json","paper":"https://pith.science/paper/WTSLSGQI"},"agent_actions":{"view_html":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX","download_json":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX.json","view_paper":"https://pith.science/paper/WTSLSGQI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2210.12217&json=true","fetch_graph":"https://pith.science/api/pith-number/WTSLSGQIPCGCCR46QFSFPLERWX/graph.json","fetch_events":"https://pith.science/api/pith-number/WTSLSGQIPCGCCR46QFSFPLERWX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX/action/storage_attestation","attest_author":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX/action/author_attestation","sign_citation":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX/action/citation_signature","submit_replication":"https://pith.science/pith/WTSLSGQIPCGCCR46QFSFPLERWX/action/replication_record"}},"created_at":"2026-07-05T05:09:25.246335+00:00","updated_at":"2026-07-05T05:09:25.246335+00:00"}