{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:YAX6JSW7MAOS6P6S4YVIPSDM2G","short_pith_number":"pith:YAX6JSW7","canonical_record":{"source":{"id":"1805.10956","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-28T14:51:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"374abd8d65903fb6dc44aef36d6ba3e4ddb8eb8a6f3cb731daf383e69e2633fe","abstract_canon_sha256":"e75bfc2ae6a2ffacf69a3f42a6164e3890cf6c412945ec60a1b9cab24da9e002"},"schema_version":"1.0"},"canonical_sha256":"c02fe4cadf601d2f3fd2e62a87c86cd1ace5e69a21a0c885c49fdb554797f832","source":{"kind":"arxiv","id":"1805.10956","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10956","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10956v1","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10956","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"pith_short_12","alias_value":"YAX6JSW7MAOS","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YAX6JSW7MAOS6P6S","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YAX6JSW7","created_at":"2026-05-18T12:33:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:YAX6JSW7MAOS6P6S4YVIPSDM2G","target":"record","payload":{"canonical_record":{"source":{"id":"1805.10956","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-28T14:51:27Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"374abd8d65903fb6dc44aef36d6ba3e4ddb8eb8a6f3cb731daf383e69e2633fe","abstract_canon_sha256":"e75bfc2ae6a2ffacf69a3f42a6164e3890cf6c412945ec60a1b9cab24da9e002"},"schema_version":"1.0"},"canonical_sha256":"c02fe4cadf601d2f3fd2e62a87c86cd1ace5e69a21a0c885c49fdb554797f832","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:14:48.704212Z","signature_b64":"kAltdY8LVABDvmM4/PM9QQVF40jOLN9q49KOv4Q/UcYiyeqOlaNPFfOJL2Id51886+UNAASGO6O8WLLaNoItBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c02fe4cadf601d2f3fd2e62a87c86cd1ace5e69a21a0c885c49fdb554797f832","last_reissued_at":"2026-05-18T00:14:48.703570Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:14:48.703570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1805.10956","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":"2026-05-18T00:14:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WujaluaR0+ZQwU62HOBk1XQnmf5y9PEEaM+RFNaIBlHUVDt5NwphZxO5+/tZlYylcU6AVfUuHCNwwmVT32/cBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:54:14.315765Z"},"content_sha256":"a309140ae3e6587e289d523deb0ec7db35dc4ee88f964f854878124968036a8a","schema_version":"1.0","event_id":"sha256:a309140ae3e6587e289d523deb0ec7db35dc4ee88f964f854878124968036a8a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:YAX6JSW7MAOS6P6S4YVIPSDM2G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Temporal Event Knowledge Acquisition via Identifying Narratives","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Ruihong Huang, Wenlin Yao","submitted_at":"2018-05-28T14:51:27Z","abstract_excerpt":"Inspired by the double temporality characteristic of narrative texts, we propose a novel approach for acquiring rich temporal \"before/after\" event knowledge across sentences in narrative stories. The double temporality states that a narrative story often describes a sequence of events following the chronological order and therefore, the temporal order of events matches with their textual order. We explored narratology principles and built a weakly supervised approach that identifies 287k narrative paragraphs from three large text corpora. We then extracted rich temporal event knowledge from th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10956","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":""},"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":"2026-05-18T00:14:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BzQHBQcYcsSVkLWdkMLLiOKAh7I6dfZ8HRORJlCYYCD5auCH52VJaQJHwMFG1EAU8LD5zuOZq/sybcIp0EyfDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T22:54:14.316185Z"},"content_sha256":"708e6a409d882dd8014b034d0b4a26ddf979ea19e857e2786645330a0551a6d2","schema_version":"1.0","event_id":"sha256:708e6a409d882dd8014b034d0b4a26ddf979ea19e857e2786645330a0551a6d2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/bundle.json","state_url":"https://pith.science/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/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":"2026-05-27T22:54:14Z","links":{"resolver":"https://pith.science/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G","bundle":"https://pith.science/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/bundle.json","state":"https://pith.science/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YAX6JSW7MAOS6P6S4YVIPSDM2G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:YAX6JSW7MAOS6P6S4YVIPSDM2G","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":"e75bfc2ae6a2ffacf69a3f42a6164e3890cf6c412945ec60a1b9cab24da9e002","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-28T14:51:27Z","title_canon_sha256":"374abd8d65903fb6dc44aef36d6ba3e4ddb8eb8a6f3cb731daf383e69e2633fe"},"schema_version":"1.0","source":{"id":"1805.10956","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.10956","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"arxiv_version","alias_value":"1805.10956v1","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.10956","created_at":"2026-05-18T00:14:48Z"},{"alias_kind":"pith_short_12","alias_value":"YAX6JSW7MAOS","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_16","alias_value":"YAX6JSW7MAOS6P6S","created_at":"2026-05-18T12:33:04Z"},{"alias_kind":"pith_short_8","alias_value":"YAX6JSW7","created_at":"2026-05-18T12:33:04Z"}],"graph_snapshots":[{"event_id":"sha256:708e6a409d882dd8014b034d0b4a26ddf979ea19e857e2786645330a0551a6d2","target":"graph","created_at":"2026-05-18T00:14:48Z","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":"Inspired by the double temporality characteristic of narrative texts, we propose a novel approach for acquiring rich temporal \"before/after\" event knowledge across sentences in narrative stories. The double temporality states that a narrative story often describes a sequence of events following the chronological order and therefore, the temporal order of events matches with their textual order. We explored narratology principles and built a weakly supervised approach that identifies 287k narrative paragraphs from three large text corpora. We then extracted rich temporal event knowledge from th","authors_text":"Ruihong Huang, Wenlin Yao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-28T14:51:27Z","title":"Temporal Event Knowledge Acquisition via Identifying Narratives"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.10956","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:a309140ae3e6587e289d523deb0ec7db35dc4ee88f964f854878124968036a8a","target":"record","created_at":"2026-05-18T00:14:48Z","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":"e75bfc2ae6a2ffacf69a3f42a6164e3890cf6c412945ec60a1b9cab24da9e002","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2018-05-28T14:51:27Z","title_canon_sha256":"374abd8d65903fb6dc44aef36d6ba3e4ddb8eb8a6f3cb731daf383e69e2633fe"},"schema_version":"1.0","source":{"id":"1805.10956","kind":"arxiv","version":1}},"canonical_sha256":"c02fe4cadf601d2f3fd2e62a87c86cd1ace5e69a21a0c885c49fdb554797f832","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c02fe4cadf601d2f3fd2e62a87c86cd1ace5e69a21a0c885c49fdb554797f832","first_computed_at":"2026-05-18T00:14:48.703570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:14:48.703570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kAltdY8LVABDvmM4/PM9QQVF40jOLN9q49KOv4Q/UcYiyeqOlaNPFfOJL2Id51886+UNAASGO6O8WLLaNoItBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:14:48.704212Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.10956","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a309140ae3e6587e289d523deb0ec7db35dc4ee88f964f854878124968036a8a","sha256:708e6a409d882dd8014b034d0b4a26ddf979ea19e857e2786645330a0551a6d2"],"state_sha256":"c273702c756afc4a6060c6bf68928809b2c2b5a143d0cc7c619f2418b32bfec2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V20JP9oROd38MhDlEd6+yG/o/dUwRLXrqtXJ8H9uGHfdogFzQ/SaXFkTTgxQSQqnmdWRntSgxRa3xjww+Lh0DQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T22:54:14.319357Z","bundle_sha256":"249c2db9b53d58676f1e031f09d1d3b7b80f6dd45bd76ce05cabf5a2187de42a"}}