{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:DXI7ECNXDOUGJG7NPP526FEMOR","short_pith_number":"pith:DXI7ECNX","canonical_record":{"source":{"id":"2203.11054","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-21T15:26:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"865abd7443016b49711e0bee68a265861a4294501d35dcf05a8abde1f981910d","abstract_canon_sha256":"551e2e26c8b2ca9e9f879df755a1e07180b35ea06dc373b4e51895c3ee3fcdc8"},"schema_version":"1.0"},"canonical_sha256":"1dd1f209b71ba8649bed7bfbaf148c7473851c150731c11064798d5aead392c7","source":{"kind":"arxiv","id":"2203.11054","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.11054","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"arxiv_version","alias_value":"2203.11054v1","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.11054","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_12","alias_value":"DXI7ECNXDOUG","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_16","alias_value":"DXI7ECNXDOUGJG7N","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_8","alias_value":"DXI7ECNX","created_at":"2026-07-05T04:07:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:DXI7ECNXDOUGJG7NPP526FEMOR","target":"record","payload":{"canonical_record":{"source":{"id":"2203.11054","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-21T15:26:35Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"865abd7443016b49711e0bee68a265861a4294501d35dcf05a8abde1f981910d","abstract_canon_sha256":"551e2e26c8b2ca9e9f879df755a1e07180b35ea06dc373b4e51895c3ee3fcdc8"},"schema_version":"1.0"},"canonical_sha256":"1dd1f209b71ba8649bed7bfbaf148c7473851c150731c11064798d5aead392c7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:07:00.271578Z","signature_b64":"MtJ+43cnCiO8clhqB79RzFmbNcMvLgBzP5569sskW1SwM+dP180B6iOb5Sje12rzjPc6YsLcs9k4SOxBG905Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1dd1f209b71ba8649bed7bfbaf148c7473851c150731c11064798d5aead392c7","last_reissued_at":"2026-07-05T04:07:00.271124Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:07:00.271124Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2203.11054","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:07:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7mBk+R3LMLRt7tA7Tjoj5bqDyMk36jh4Td+uoJIUtLpZJ52RALz3OmKDU07/YfETtg+vyXv7dE3+YtHdMEcRDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:22:20.303018Z"},"content_sha256":"9579efdd6d7865d013734d70a3e953f0bb0b939a5b7e8fe3e2e423929c7c6bfd","schema_version":"1.0","event_id":"sha256:9579efdd6d7865d013734d70a3e953f0bb0b939a5b7e8fe3e2e423929c7c6bfd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:DXI7ECNXDOUGJG7NPP526FEMOR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Dinesh Khandelwal, Hima Karanam, L Venkata Subramaniam, Nithish Kannen, Shajith Ikbal, Sumit Neelam, Udit Sharma","submitted_at":"2022-03-21T15:26:35Z","abstract_excerpt":"Knowledge Base Question Answering (KBQA) systems have the goal of answering complex natural language questions by reasoning over relevant facts retrieved from Knowledge Bases (KB). One of the major challenges faced by these systems is their inability to retrieve all relevant facts due to factors such as incomplete KB and entity/relation linking errors. In this paper, we address this particular challenge for systems handling a specific category of questions called temporal questions, where answer derivation involve reasoning over facts asserting point/intervals of time for various events. We pr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.11054","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/2203.11054/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:07:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"95Et8gfXsC5amhMzWEvhqFOF6PiDdWvOKh2W6H8xtH8+PiWiT9N9HTcTWiW94MbGvXR6g2T9KKm+a52FJKVlBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-11T08:22:20.303409Z"},"content_sha256":"2b58c6f1075bfbfd878c6a1c748d1d529728ed555a297f8575ac75f1158c8cbe","schema_version":"1.0","event_id":"sha256:2b58c6f1075bfbfd878c6a1c748d1d529728ed555a297f8575ac75f1158c8cbe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DXI7ECNXDOUGJG7NPP526FEMOR/bundle.json","state_url":"https://pith.science/pith/DXI7ECNXDOUGJG7NPP526FEMOR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DXI7ECNXDOUGJG7NPP526FEMOR/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":"2026-07-11T08:22:20Z","links":{"resolver":"https://pith.science/pith/DXI7ECNXDOUGJG7NPP526FEMOR","bundle":"https://pith.science/pith/DXI7ECNXDOUGJG7NPP526FEMOR/bundle.json","state":"https://pith.science/pith/DXI7ECNXDOUGJG7NPP526FEMOR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DXI7ECNXDOUGJG7NPP526FEMOR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:DXI7ECNXDOUGJG7NPP526FEMOR","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":"551e2e26c8b2ca9e9f879df755a1e07180b35ea06dc373b4e51895c3ee3fcdc8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-21T15:26:35Z","title_canon_sha256":"865abd7443016b49711e0bee68a265861a4294501d35dcf05a8abde1f981910d"},"schema_version":"1.0","source":{"id":"2203.11054","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.11054","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"arxiv_version","alias_value":"2203.11054v1","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.11054","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_12","alias_value":"DXI7ECNXDOUG","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_16","alias_value":"DXI7ECNXDOUGJG7N","created_at":"2026-07-05T04:07:00Z"},{"alias_kind":"pith_short_8","alias_value":"DXI7ECNX","created_at":"2026-07-05T04:07:00Z"}],"graph_snapshots":[{"event_id":"sha256:2b58c6f1075bfbfd878c6a1c748d1d529728ed555a297f8575ac75f1158c8cbe","target":"graph","created_at":"2026-07-05T04:07:00Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2203.11054/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge Base Question Answering (KBQA) systems have the goal of answering complex natural language questions by reasoning over relevant facts retrieved from Knowledge Bases (KB). One of the major challenges faced by these systems is their inability to retrieve all relevant facts due to factors such as incomplete KB and entity/relation linking errors. In this paper, we address this particular challenge for systems handling a specific category of questions called temporal questions, where answer derivation involve reasoning over facts asserting point/intervals of time for various events. We pr","authors_text":"Dinesh Khandelwal, Hima Karanam, L Venkata Subramaniam, Nithish Kannen, Shajith Ikbal, Sumit Neelam, Udit Sharma","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-21T15:26:35Z","title":"Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.11054","kind":"arxiv","version":1},"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":"sha256:9579efdd6d7865d013734d70a3e953f0bb0b939a5b7e8fe3e2e423929c7c6bfd","target":"record","created_at":"2026-07-05T04:07:00Z","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":"551e2e26c8b2ca9e9f879df755a1e07180b35ea06dc373b4e51895c3ee3fcdc8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2022-03-21T15:26:35Z","title_canon_sha256":"865abd7443016b49711e0bee68a265861a4294501d35dcf05a8abde1f981910d"},"schema_version":"1.0","source":{"id":"2203.11054","kind":"arxiv","version":1}},"canonical_sha256":"1dd1f209b71ba8649bed7bfbaf148c7473851c150731c11064798d5aead392c7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1dd1f209b71ba8649bed7bfbaf148c7473851c150731c11064798d5aead392c7","first_computed_at":"2026-07-05T04:07:00.271124Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:07:00.271124Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MtJ+43cnCiO8clhqB79RzFmbNcMvLgBzP5569sskW1SwM+dP180B6iOb5Sje12rzjPc6YsLcs9k4SOxBG905Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:07:00.271578Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.11054","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9579efdd6d7865d013734d70a3e953f0bb0b939a5b7e8fe3e2e423929c7c6bfd","sha256:2b58c6f1075bfbfd878c6a1c748d1d529728ed555a297f8575ac75f1158c8cbe"],"state_sha256":"f9593b685c4f068f614a8ac55a3edf8b8efddbbb86e68cfcc24c79e6b02be66f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OzFGZY8tRxaLAHtzshqvomuPE50tCv/CKaQ+6U93eU2JFNGHy/5JqsJnVGqtVHRLN4rQaDrCmoEHbNwQ7Bs3Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-11T08:22:20.305876Z","bundle_sha256":"68a5ac98800e94d2175f7aab21ecf89f8ccbf5786539b4280987b9b36d99531c"}}