{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WCD3QORTP333EFKAZIU3OBSVM7","short_pith_number":"pith:WCD3QORT","canonical_record":{"source":{"id":"2605.15904","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T12:42:47Z","cross_cats_sorted":[],"title_canon_sha256":"91feb6a633a7b5e540922da4552bd233b02b2f32dd031ef56e19cc0ec75372da","abstract_canon_sha256":"a32b2f6486b44da7a5a2732ea6b48f09d18553fe550ccc46a244d3d1da4bd872"},"schema_version":"1.0"},"canonical_sha256":"b087b83a337ef7b21540ca29b7065567fbaa2c6dce95fd143819d6fde874328c","source":{"kind":"arxiv","id":"2605.15904","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15904","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15904v1","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15904","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_12","alias_value":"WCD3QORTP333","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_16","alias_value":"WCD3QORTP333EFKA","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_8","alias_value":"WCD3QORT","created_at":"2026-05-20T00:01:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WCD3QORTP333EFKAZIU3OBSVM7","target":"record","payload":{"canonical_record":{"source":{"id":"2605.15904","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T12:42:47Z","cross_cats_sorted":[],"title_canon_sha256":"91feb6a633a7b5e540922da4552bd233b02b2f32dd031ef56e19cc0ec75372da","abstract_canon_sha256":"a32b2f6486b44da7a5a2732ea6b48f09d18553fe550ccc46a244d3d1da4bd872"},"schema_version":"1.0"},"canonical_sha256":"b087b83a337ef7b21540ca29b7065567fbaa2c6dce95fd143819d6fde874328c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:01:24.710953Z","signature_b64":"LEm4W/ECwPKxEmETRqDVM5v9wrBEVhh69fpcKYwPsMisKvHAFBt4FRMojKjhkVn2HhRXYt2f0BJhFIzXQRWcAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b087b83a337ef7b21540ca29b7065567fbaa2c6dce95fd143819d6fde874328c","last_reissued_at":"2026-05-20T00:01:24.710271Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:01:24.710271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.15904","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":"2026-05-20T00:01:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"i36yvi158Fje0vCnEKXuHlnDPZuSMex/fI1P25aL1bPEGaILrEsEOw+RFw2JcL775JgwhLGb/jprrs2QSPeFDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:09:29.781572Z"},"content_sha256":"723ffc0a0a5df74ee471e11883a6e70c5bef63c3d41a743bf4b620dd42f61eb0","schema_version":"1.0","event_id":"sha256:723ffc0a0a5df74ee471e11883a6e70c5bef63c3d41a743bf4b620dd42f61eb0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WCD3QORTP333EFKAZIU3OBSVM7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Context-aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Inoussa Mouiche, Sherif Saad","submitted_at":"2026-05-15T12:42:47Z","abstract_excerpt":"Cybersecurity Knowledge Graphs (CKGs) unify diverse Cyber Threat Intelligence (CTI) sources into structured, queryable formats, offering scalable solutions for automating proactive and real-time security responses. Their increasing adoption has significantly enhanced the workflow and decision-making efficiency of security professionals. However, constructing CKGs requires extracting entity-relation triples from unstructured CTI reports, a task hindered by complex report structure, domain-specific language, and semantic ambiguity. As a result, existing pipeline-based approaches often suffer fro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.15904","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/2605.15904/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:46.562814Z","status":"skipped","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T17:01:55.769410Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"0584f25919a814ad741461e98ff801056bebf6611894ef4271aa668bd59f1071"},"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":"2026-05-20T00:01:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"54sm8i/zScNB+f8M9Th0Y11LBcK0r/7tn72NLEqbBpvyDmTAVycW6i1rDF7rkceZlniZStVqk7gaarcJU0w/AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T20:09:29.782268Z"},"content_sha256":"e357379c581c81797e23b98dcdc7427a7df58f101ab39776e39a67c64e064492","schema_version":"1.0","event_id":"sha256:e357379c581c81797e23b98dcdc7427a7df58f101ab39776e39a67c64e064492"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WCD3QORTP333EFKAZIU3OBSVM7/bundle.json","state_url":"https://pith.science/pith/WCD3QORTP333EFKAZIU3OBSVM7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WCD3QORTP333EFKAZIU3OBSVM7/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":"2026-05-27T20:09:29Z","links":{"resolver":"https://pith.science/pith/WCD3QORTP333EFKAZIU3OBSVM7","bundle":"https://pith.science/pith/WCD3QORTP333EFKAZIU3OBSVM7/bundle.json","state":"https://pith.science/pith/WCD3QORTP333EFKAZIU3OBSVM7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WCD3QORTP333EFKAZIU3OBSVM7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WCD3QORTP333EFKAZIU3OBSVM7","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":"a32b2f6486b44da7a5a2732ea6b48f09d18553fe550ccc46a244d3d1da4bd872","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T12:42:47Z","title_canon_sha256":"91feb6a633a7b5e540922da4552bd233b02b2f32dd031ef56e19cc0ec75372da"},"schema_version":"1.0","source":{"id":"2605.15904","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.15904","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"arxiv_version","alias_value":"2605.15904v1","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.15904","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_12","alias_value":"WCD3QORTP333","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_16","alias_value":"WCD3QORTP333EFKA","created_at":"2026-05-20T00:01:24Z"},{"alias_kind":"pith_short_8","alias_value":"WCD3QORT","created_at":"2026-05-20T00:01:24Z"}],"graph_snapshots":[{"event_id":"sha256:e357379c581c81797e23b98dcdc7427a7df58f101ab39776e39a67c64e064492","target":"graph","created_at":"2026-05-20T00:01:24Z","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":[{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T17:33:46.562814Z","status":"skipped","version":"1.0.0"},{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T17:01:55.769410Z","status":"completed","version":"1.0.0"}],"endpoint":"/pith/2605.15904/integrity.json","findings":[],"snapshot_sha256":"0584f25919a814ad741461e98ff801056bebf6611894ef4271aa668bd59f1071","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Cybersecurity Knowledge Graphs (CKGs) unify diverse Cyber Threat Intelligence (CTI) sources into structured, queryable formats, offering scalable solutions for automating proactive and real-time security responses. Their increasing adoption has significantly enhanced the workflow and decision-making efficiency of security professionals. However, constructing CKGs requires extracting entity-relation triples from unstructured CTI reports, a task hindered by complex report structure, domain-specific language, and semantic ambiguity. As a result, existing pipeline-based approaches often suffer fro","authors_text":"Inoussa Mouiche, Sherif Saad","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T12:42:47Z","title":"Context-aware Entity-Relation Extraction for Threat Intelligence Knowledge Graphs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.15904","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":"sha256:723ffc0a0a5df74ee471e11883a6e70c5bef63c3d41a743bf4b620dd42f61eb0","target":"record","created_at":"2026-05-20T00:01:24Z","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":"a32b2f6486b44da7a5a2732ea6b48f09d18553fe550ccc46a244d3d1da4bd872","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-05-15T12:42:47Z","title_canon_sha256":"91feb6a633a7b5e540922da4552bd233b02b2f32dd031ef56e19cc0ec75372da"},"schema_version":"1.0","source":{"id":"2605.15904","kind":"arxiv","version":1}},"canonical_sha256":"b087b83a337ef7b21540ca29b7065567fbaa2c6dce95fd143819d6fde874328c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b087b83a337ef7b21540ca29b7065567fbaa2c6dce95fd143819d6fde874328c","first_computed_at":"2026-05-20T00:01:24.710271Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:01:24.710271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LEm4W/ECwPKxEmETRqDVM5v9wrBEVhh69fpcKYwPsMisKvHAFBt4FRMojKjhkVn2HhRXYt2f0BJhFIzXQRWcAQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:01:24.710953Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.15904","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:723ffc0a0a5df74ee471e11883a6e70c5bef63c3d41a743bf4b620dd42f61eb0","sha256:e357379c581c81797e23b98dcdc7427a7df58f101ab39776e39a67c64e064492"],"state_sha256":"ca6d42301e3badb98308867af74cf6db7f41cab5781b0def17207c03f1a5b8b8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3GjI83v6W7GRR8HXdfVe+VMK5JaLgyQ8apboyuaqrBGztBGk8a9+DeIMLmnavW5nfL4cqccJlCTpOk5Ylx8kAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T20:09:29.784802Z","bundle_sha256":"2b620edac78a09d5097d2990f5c5961f6a9091b3b3223b4945f811ca03ab6012"}}