{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:B5MZ467K4XZ6TMJPJKPB4KVOEH","short_pith_number":"pith:B5MZ467K","canonical_record":{"source":{"id":"1806.02455","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-06T23:12:02Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b7d925c0d908b7ee4995efd7126d715a126294af5c176f60a0ccf326a38fae7c","abstract_canon_sha256":"21b51f07e1f878320821a2109e5555985c9c36bb8c51aef1ef91388e48817e7b"},"schema_version":"1.0"},"canonical_sha256":"0f599e7beae5f3e9b12f4a9e1e2aae21e20869d821acae0331a5f12baf0ae345","source":{"kind":"arxiv","id":"1806.02455","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02455","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02455v2","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02455","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"B5MZ467K4XZ6","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B5MZ467K4XZ6TMJP","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B5MZ467K","created_at":"2026-05-18T12:32:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:B5MZ467K4XZ6TMJPJKPB4KVOEH","target":"record","payload":{"canonical_record":{"source":{"id":"1806.02455","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-06T23:12:02Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"b7d925c0d908b7ee4995efd7126d715a126294af5c176f60a0ccf326a38fae7c","abstract_canon_sha256":"21b51f07e1f878320821a2109e5555985c9c36bb8c51aef1ef91388e48817e7b"},"schema_version":"1.0"},"canonical_sha256":"0f599e7beae5f3e9b12f4a9e1e2aae21e20869d821acae0331a5f12baf0ae345","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:44.286402Z","signature_b64":"GAnYPaevtQPMg0zodU5o+fOVlXl3Bx1G6b5yJAmDYUfOczPsWyFxwm72zI1Wg/StYDEWUhRf0P8c7gJveIvlBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0f599e7beae5f3e9b12f4a9e1e2aae21e20869d821acae0331a5f12baf0ae345","last_reissued_at":"2026-05-17T23:47:44.285775Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:44.285775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1806.02455","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"idnwMU3Od9wl5e7Fic2SjMyIZlvzj0u92TitvtdocgUglXamL11+bQ8UwtHSDZbyOyDi0eMbqSiirBAA70S6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:42:43.114826Z"},"content_sha256":"70fc847ef3f51b9453398781588b2766ed953df7cf61c45ab0b91655fa2ef12b","schema_version":"1.0","event_id":"sha256:70fc847ef3f51b9453398781588b2766ed953df7cf61c45ab0b91655fa2ef12b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:B5MZ467K4XZ6TMJPJKPB4KVOEH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Cheol Young Park, Kathryn Blackmond Laskey","submitted_at":"2018-06-06T23:12:02Z","abstract_excerpt":"Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning. Developing a MEBN model to support a given application is a challenge, requiring definition of entities, relationships, random variables, conditional dependence relationships, and probability distributions. When available, data can be invaluable both to improve performance and to streamline development. By far the most common format for available data is the re"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02455","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-17T23:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lcahs8D27QVAlIWax73yZyeyghKMHWjVedu0k5LdlbtCyiBMa+lbyFMWt8p0vacTZ6wY5cPgp5lNEwAdvdGoAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T00:42:43.115501Z"},"content_sha256":"c205a53f2d77f48a813dde19b3619d8eae5b005a9867a6c5a0e0bfdff87e882c","schema_version":"1.0","event_id":"sha256:c205a53f2d77f48a813dde19b3619d8eae5b005a9867a6c5a0e0bfdff87e882c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/bundle.json","state_url":"https://pith.science/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-27T00:42:43Z","links":{"resolver":"https://pith.science/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH","bundle":"https://pith.science/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/bundle.json","state":"https://pith.science/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B5MZ467K4XZ6TMJPJKPB4KVOEH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:B5MZ467K4XZ6TMJPJKPB4KVOEH","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"21b51f07e1f878320821a2109e5555985c9c36bb8c51aef1ef91388e48817e7b","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-06T23:12:02Z","title_canon_sha256":"b7d925c0d908b7ee4995efd7126d715a126294af5c176f60a0ccf326a38fae7c"},"schema_version":"1.0","source":{"id":"1806.02455","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1806.02455","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"1806.02455v2","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1806.02455","created_at":"2026-05-17T23:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"B5MZ467K4XZ6","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_16","alias_value":"B5MZ467K4XZ6TMJP","created_at":"2026-05-18T12:32:13Z"},{"alias_kind":"pith_short_8","alias_value":"B5MZ467K","created_at":"2026-05-18T12:32:13Z"}],"graph_snapshots":[{"event_id":"sha256:c205a53f2d77f48a813dde19b3619d8eae5b005a9867a6c5a0e0bfdff87e882c","target":"graph","created_at":"2026-05-17T23:47:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Multi-Entity Bayesian Network (MEBN) is a knowledge representation formalism combining Bayesian Networks (BN) with First-Order Logic (FOL). MEBN has sufficient expressive power for general-purpose knowledge representation and reasoning. Developing a MEBN model to support a given application is a challenge, requiring definition of entities, relationships, random variables, conditional dependence relationships, and probability distributions. When available, data can be invaluable both to improve performance and to streamline development. By far the most common format for available data is the re","authors_text":"Cheol Young Park, Kathryn Blackmond Laskey","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-06T23:12:02Z","title":"MEBN-RM: A Mapping between Multi-Entity Bayesian Network and Relational Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1806.02455","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:70fc847ef3f51b9453398781588b2766ed953df7cf61c45ab0b91655fa2ef12b","target":"record","created_at":"2026-05-17T23:47:44Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"21b51f07e1f878320821a2109e5555985c9c36bb8c51aef1ef91388e48817e7b","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-06-06T23:12:02Z","title_canon_sha256":"b7d925c0d908b7ee4995efd7126d715a126294af5c176f60a0ccf326a38fae7c"},"schema_version":"1.0","source":{"id":"1806.02455","kind":"arxiv","version":2}},"canonical_sha256":"0f599e7beae5f3e9b12f4a9e1e2aae21e20869d821acae0331a5f12baf0ae345","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f599e7beae5f3e9b12f4a9e1e2aae21e20869d821acae0331a5f12baf0ae345","first_computed_at":"2026-05-17T23:47:44.285775Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:47:44.285775Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GAnYPaevtQPMg0zodU5o+fOVlXl3Bx1G6b5yJAmDYUfOczPsWyFxwm72zI1Wg/StYDEWUhRf0P8c7gJveIvlBA==","signature_status":"signed_v1","signed_at":"2026-05-17T23:47:44.286402Z","signed_message":"canonical_sha256_bytes"},"source_id":"1806.02455","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:70fc847ef3f51b9453398781588b2766ed953df7cf61c45ab0b91655fa2ef12b","sha256:c205a53f2d77f48a813dde19b3619d8eae5b005a9867a6c5a0e0bfdff87e882c"],"state_sha256":"33b2d756d08c60237741d527f6d4081b44caab79491b6f3228c2b40c8c664adb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hMDcmehFM3ThBl1/D+5VczFxqR2fmXBXS69cONH5kLK1O7pCKDHQkcFP6TInAPJHvdQ5XHc4ngSBGO5cOlNLBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T00:42:43.118611Z","bundle_sha256":"55cd24790600658583e3c09679128dd05eba104b9ca85d89193163c77b1179d4"}}