{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:X35WWTE5BKPOI4ONQJMRICMXWA","short_pith_number":"pith:X35WWTE5","canonical_record":{"source":{"id":"1809.05724","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-15T14:37:46Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"346bea5f5b70dd6380fe097ee87d172ba99b85eec20fdf8f99990f01166fa03f","abstract_canon_sha256":"cde6a7cfa4eba3efb2a3f381b5b60276c7d7415e1a16161eb551ad16110d8c96"},"schema_version":"1.0"},"canonical_sha256":"befb6b4c9d0a9ee471cd8259140997b036002c90fa57ce433361b7675d4cccf9","source":{"kind":"arxiv","id":"1809.05724","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.05724","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"1809.05724v2","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.05724","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"X35WWTE5BKPO","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X35WWTE5BKPOI4ON","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X35WWTE5","created_at":"2026-05-18T12:33:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:X35WWTE5BKPOI4ONQJMRICMXWA","target":"record","payload":{"canonical_record":{"source":{"id":"1809.05724","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-15T14:37:46Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"346bea5f5b70dd6380fe097ee87d172ba99b85eec20fdf8f99990f01166fa03f","abstract_canon_sha256":"cde6a7cfa4eba3efb2a3f381b5b60276c7d7415e1a16161eb551ad16110d8c96"},"schema_version":"1.0"},"canonical_sha256":"befb6b4c9d0a9ee471cd8259140997b036002c90fa57ce433361b7675d4cccf9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:18.036392Z","signature_b64":"FYO1P33yfGP+ossqYnv5vNQsmG+m+9cyIM2xltEqq4mos0w87i0lveZxyqLsu7EnoBhSFb4ia64V9DhKFjlCBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"befb6b4c9d0a9ee471cd8259140997b036002c90fa57ce433361b7675d4cccf9","last_reissued_at":"2026-05-18T00:00:18.035738Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:18.035738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1809.05724","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":"2026-05-18T00:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fOURVX5YBEFtsFN/G59kw7aAIKsZDjTLHkce6/oE5VV+tupFMYOrbZzKC2ZYy4hF4Au8Q0TLGToEy9wuV0JiBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T06:22:48.598904Z"},"content_sha256":"15b690638dfacdc498248e196bf7cb47649026d1de9ed612c7fa6869989ed06d","schema_version":"1.0","event_id":"sha256:15b690638dfacdc498248e196bf7cb47649026d1de9ed612c7fa6869989ed06d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:X35WWTE5BKPOI4ONQJMRICMXWA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Improving Natural Language Inference Using External Knowledge in the Science Questions Domain","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AI","authors_text":"Achille Fokoue, Bassem Makni, Ibrahim Abdelaziz, Kartik Talamadupula, Maria Chang, Michael Witbrock, Mo Yu, Nicholas Mattei, Pavan Kapanipathi, Ryan Musa, Xiaoyan Wang","submitted_at":"2018-09-15T14:37:46Z","abstract_excerpt":"Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained significant attention thanks to the release of large scale, challenging datasets. Present approaches to the problem largely focus on learning-based methods that use only textual information in order to classify whether a given premise entails, contradicts, or is neutral with respect to a given hypothesis. Surprisingly, the use of methods based on structured knowledge -- a central topic in artificial intelligence -- h"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.05724","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":"2026-05-18T00:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sTrmC9TSE2oZJKdPcLSOthEVvMBjQuCjG4D9cIiT8aTHgVJmkGzfoI8wp/ZjYhw4xASv+cI+upHxcvAHc6/FCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-28T06:22:48.599257Z"},"content_sha256":"217c887f7447c25455735074f6346c1f3a0b181b2f1d46c50c018f1a1951e644","schema_version":"1.0","event_id":"sha256:217c887f7447c25455735074f6346c1f3a0b181b2f1d46c50c018f1a1951e644"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/X35WWTE5BKPOI4ONQJMRICMXWA/bundle.json","state_url":"https://pith.science/pith/X35WWTE5BKPOI4ONQJMRICMXWA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/X35WWTE5BKPOI4ONQJMRICMXWA/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":"2026-05-28T06:22:48Z","links":{"resolver":"https://pith.science/pith/X35WWTE5BKPOI4ONQJMRICMXWA","bundle":"https://pith.science/pith/X35WWTE5BKPOI4ONQJMRICMXWA/bundle.json","state":"https://pith.science/pith/X35WWTE5BKPOI4ONQJMRICMXWA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/X35WWTE5BKPOI4ONQJMRICMXWA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:X35WWTE5BKPOI4ONQJMRICMXWA","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":"cde6a7cfa4eba3efb2a3f381b5b60276c7d7415e1a16161eb551ad16110d8c96","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-15T14:37:46Z","title_canon_sha256":"346bea5f5b70dd6380fe097ee87d172ba99b85eec20fdf8f99990f01166fa03f"},"schema_version":"1.0","source":{"id":"1809.05724","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1809.05724","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"1809.05724v2","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.05724","created_at":"2026-05-18T00:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"X35WWTE5BKPO","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_16","alias_value":"X35WWTE5BKPOI4ON","created_at":"2026-05-18T12:33:01Z"},{"alias_kind":"pith_short_8","alias_value":"X35WWTE5","created_at":"2026-05-18T12:33:01Z"}],"graph_snapshots":[{"event_id":"sha256:217c887f7447c25455735074f6346c1f3a0b181b2f1d46c50c018f1a1951e644","target":"graph","created_at":"2026-05-18T00:00:18Z","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":"Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained significant attention thanks to the release of large scale, challenging datasets. Present approaches to the problem largely focus on learning-based methods that use only textual information in order to classify whether a given premise entails, contradicts, or is neutral with respect to a given hypothesis. Surprisingly, the use of methods based on structured knowledge -- a central topic in artificial intelligence -- h","authors_text":"Achille Fokoue, Bassem Makni, Ibrahim Abdelaziz, Kartik Talamadupula, Maria Chang, Michael Witbrock, Mo Yu, Nicholas Mattei, Pavan Kapanipathi, Ryan Musa, Xiaoyan Wang","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-15T14:37:46Z","title":"Improving Natural Language Inference Using External Knowledge in the Science Questions Domain"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.05724","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":"sha256:15b690638dfacdc498248e196bf7cb47649026d1de9ed612c7fa6869989ed06d","target":"record","created_at":"2026-05-18T00:00:18Z","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":"cde6a7cfa4eba3efb2a3f381b5b60276c7d7415e1a16161eb551ad16110d8c96","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2018-09-15T14:37:46Z","title_canon_sha256":"346bea5f5b70dd6380fe097ee87d172ba99b85eec20fdf8f99990f01166fa03f"},"schema_version":"1.0","source":{"id":"1809.05724","kind":"arxiv","version":2}},"canonical_sha256":"befb6b4c9d0a9ee471cd8259140997b036002c90fa57ce433361b7675d4cccf9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"befb6b4c9d0a9ee471cd8259140997b036002c90fa57ce433361b7675d4cccf9","first_computed_at":"2026-05-18T00:00:18.035738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:18.035738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FYO1P33yfGP+ossqYnv5vNQsmG+m+9cyIM2xltEqq4mos0w87i0lveZxyqLsu7EnoBhSFb4ia64V9DhKFjlCBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:18.036392Z","signed_message":"canonical_sha256_bytes"},"source_id":"1809.05724","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:15b690638dfacdc498248e196bf7cb47649026d1de9ed612c7fa6869989ed06d","sha256:217c887f7447c25455735074f6346c1f3a0b181b2f1d46c50c018f1a1951e644"],"state_sha256":"f15aa9e42eaa011a086b3cda02e39442e752d03709def378679e0ca96243e52e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yit2HzNY94PFSxJdea5QoyDcRqQTpDpmhbsqFRfqppMqLwQW2kyYcyTIfd6QcvZy1OdCyZeKGDSicNN2YWPhAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-28T06:22:48.601404Z","bundle_sha256":"7022e3b50751e1db43fe7ff6a1cba7f926b86faf1a1ed44b56180db127eaf2d8"}}