{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2010:OLBULA3NEFQGRRERSLU5C3YQA4","short_pith_number":"pith:OLBULA3N","schema_version":"1.0","canonical_sha256":"72c345836d216068c49192e9d16f10071c41394316c55933de3231a3e6856968","source":{"kind":"arxiv","id":"1009.3798","version":2},"attestation_state":"computed","paper":{"title":"DNF Sampling for ProbLog Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LO","authors_text":"Angelika Kimmig, Dimitar Sht. Shterionov, Gerda Janssens, Theofrastos Mantadelis","submitted_at":"2010-09-20T12:45:09Z","abstract_excerpt":"Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduction to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computationally hard. In this work we introduce a new approximation method for ProbLog inference which exploits the DNF to focus sampling. While this DNF sampling technique has been applied to a variety of tasks before, to the best of our knowledge it has not been used for inference in probabilistic logic systems. The paper also prese"},"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":"1009.3798","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LO","submitted_at":"2010-09-20T12:45:09Z","cross_cats_sorted":[],"title_canon_sha256":"5164eb56a52511b48f9b2b9e195ac217f996344e9611a9ae29a1f50aa3cb6dff","abstract_canon_sha256":"23142a6c44797e40e3b902bc4afd9824f163c09c44120019f295c95059c00d34"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:40:34.890443Z","signature_b64":"zvVRpTQ9P+ztM5FFICuTa6g1UCRYBss0nsnF4Is3iFhQNt6i/Gmobyeq84U+5B4ZMQdh5GK5Db7iW1ovd9SLAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72c345836d216068c49192e9d16f10071c41394316c55933de3231a3e6856968","last_reissued_at":"2026-05-18T04:40:34.889824Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:40:34.889824Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"DNF Sampling for ProbLog Inference","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LO","authors_text":"Angelika Kimmig, Dimitar Sht. Shterionov, Gerda Janssens, Theofrastos Mantadelis","submitted_at":"2010-09-20T12:45:09Z","abstract_excerpt":"Inference in probabilistic logic languages such as ProbLog, an extension of Prolog with probabilistic facts, is often based on a reduction to a propositional formula in DNF. Calculating the probability of such a formula involves the disjoint-sum-problem, which is computationally hard. In this work we introduce a new approximation method for ProbLog inference which exploits the DNF to focus sampling. While this DNF sampling technique has been applied to a variety of tasks before, to the best of our knowledge it has not been used for inference in probabilistic logic systems. The paper also prese"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1009.3798","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"1009.3798","created_at":"2026-05-18T04:40:34.889899+00:00"},{"alias_kind":"arxiv_version","alias_value":"1009.3798v2","created_at":"2026-05-18T04:40:34.889899+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1009.3798","created_at":"2026-05-18T04:40:34.889899+00:00"},{"alias_kind":"pith_short_12","alias_value":"OLBULA3NEFQG","created_at":"2026-05-18T12:26:12.377268+00:00"},{"alias_kind":"pith_short_16","alias_value":"OLBULA3NEFQGRRER","created_at":"2026-05-18T12:26:12.377268+00:00"},{"alias_kind":"pith_short_8","alias_value":"OLBULA3N","created_at":"2026-05-18T12:26:12.377268+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/OLBULA3NEFQGRRERSLU5C3YQA4","json":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4.json","graph_json":"https://pith.science/api/pith-number/OLBULA3NEFQGRRERSLU5C3YQA4/graph.json","events_json":"https://pith.science/api/pith-number/OLBULA3NEFQGRRERSLU5C3YQA4/events.json","paper":"https://pith.science/paper/OLBULA3N"},"agent_actions":{"view_html":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4","download_json":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4.json","view_paper":"https://pith.science/paper/OLBULA3N","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1009.3798&json=true","fetch_graph":"https://pith.science/api/pith-number/OLBULA3NEFQGRRERSLU5C3YQA4/graph.json","fetch_events":"https://pith.science/api/pith-number/OLBULA3NEFQGRRERSLU5C3YQA4/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4/action/storage_attestation","attest_author":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4/action/author_attestation","sign_citation":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4/action/citation_signature","submit_replication":"https://pith.science/pith/OLBULA3NEFQGRRERSLU5C3YQA4/action/replication_record"}},"created_at":"2026-05-18T04:40:34.889899+00:00","updated_at":"2026-05-18T04:40:34.889899+00:00"}