{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:PKLGT6NEP7WPZ6B5MYP6ZIKEVR","short_pith_number":"pith:PKLGT6NE","canonical_record":{"source":{"id":"2605.25781","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T12:29:30Z","cross_cats_sorted":[],"title_canon_sha256":"3634708ab3f55a27bc772222042ce9e9fec2b780b6fad624e5b904ed989ab679","abstract_canon_sha256":"cacdf54b67652ee7006d3cb6b82e46fc7d199a5a52ed0b6cc8d6c583f8ec30e9"},"schema_version":"1.0"},"canonical_sha256":"7a9669f9a47fecfcf83d661feca144ac664135aee40c6776e9b40a3df851f526","source":{"kind":"arxiv","id":"2605.25781","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25781","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25781v1","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25781","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_12","alias_value":"PKLGT6NEP7WP","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_16","alias_value":"PKLGT6NEP7WPZ6B5","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_8","alias_value":"PKLGT6NE","created_at":"2026-05-26T02:04:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:PKLGT6NEP7WPZ6B5MYP6ZIKEVR","target":"record","payload":{"canonical_record":{"source":{"id":"2605.25781","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T12:29:30Z","cross_cats_sorted":[],"title_canon_sha256":"3634708ab3f55a27bc772222042ce9e9fec2b780b6fad624e5b904ed989ab679","abstract_canon_sha256":"cacdf54b67652ee7006d3cb6b82e46fc7d199a5a52ed0b6cc8d6c583f8ec30e9"},"schema_version":"1.0"},"canonical_sha256":"7a9669f9a47fecfcf83d661feca144ac664135aee40c6776e9b40a3df851f526","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-26T02:04:54.363443Z","signature_b64":"G/a4LCK9xxPVdlvdeGOZH8wEYQKCjHnuz5Ux/7IzVLTDvXhfWFlCR4TBzi7ajXTGKlZxkxB22UBFymJ1ZiLpDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7a9669f9a47fecfcf83d661feca144ac664135aee40c6776e9b40a3df851f526","last_reissued_at":"2026-05-26T02:04:54.362958Z","signature_status":"signed_v1","first_computed_at":"2026-05-26T02:04:54.362958Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.25781","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":"2026-05-26T02:04:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D2VbmTZnz1NpygmQmsdHYBrSaL97F4/HexQ9QKwid0FGSBSeds5mKzgmb18AgSgA5Z8m1RwpGAj53ZjnQXyJDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T20:55:02.329497Z"},"content_sha256":"597e8cfb7220229112d3de0f84f97a9a732c96daab1417e58962a599f51c0df5","schema_version":"1.0","event_id":"sha256:597e8cfb7220229112d3de0f84f97a9a732c96daab1417e58962a599f51c0df5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:PKLGT6NEP7WPZ6B5MYP6ZIKEVR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Double Triangle Annotation: A Scalable Human-in-the-Loop Framework for High-Precision Historical Document Annotation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Yi Ren","submitted_at":"2026-05-25T12:29:30Z","abstract_excerpt":"Evaluating structured-information extraction from historical documents at scale requires high-precision ground-truth annotations, yet traditional manual labeling is expensive and fully automated pipelines built on large language models are prone to hallucination. We propose Double Triangle Annotation, a two-layer human-in-the-loop framework that leverages cross-model consensus to automate the majority of annotation work while ensuring high-precision outputs. In the first layer, two architecturally independent Multimodal Large Language Models annotate each document in parallel; when they agree,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25781","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/2605.25781/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":"2026-05-26T02:04:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tlVu9G3Sx0egBM4qvxdi3RnnvNvNzKAN4MNPlU6Bn/C6tTd0aSbwtIOnfty55LlKCji2CmF1j3+r18DPkP+1BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T20:55:02.330131Z"},"content_sha256":"2772b4b9b48320232226df0c91b282c3a2ddf28c68c85028000f088146c135d5","schema_version":"1.0","event_id":"sha256:2772b4b9b48320232226df0c91b282c3a2ddf28c68c85028000f088146c135d5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/bundle.json","state_url":"https://pith.science/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/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":"2026-06-30T20:55:02Z","links":{"resolver":"https://pith.science/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR","bundle":"https://pith.science/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/bundle.json","state":"https://pith.science/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PKLGT6NEP7WPZ6B5MYP6ZIKEVR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PKLGT6NEP7WPZ6B5MYP6ZIKEVR","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":"cacdf54b67652ee7006d3cb6b82e46fc7d199a5a52ed0b6cc8d6c583f8ec30e9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T12:29:30Z","title_canon_sha256":"3634708ab3f55a27bc772222042ce9e9fec2b780b6fad624e5b904ed989ab679"},"schema_version":"1.0","source":{"id":"2605.25781","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.25781","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"arxiv_version","alias_value":"2605.25781v1","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.25781","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_12","alias_value":"PKLGT6NEP7WP","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_16","alias_value":"PKLGT6NEP7WPZ6B5","created_at":"2026-05-26T02:04:54Z"},{"alias_kind":"pith_short_8","alias_value":"PKLGT6NE","created_at":"2026-05-26T02:04:54Z"}],"graph_snapshots":[{"event_id":"sha256:2772b4b9b48320232226df0c91b282c3a2ddf28c68c85028000f088146c135d5","target":"graph","created_at":"2026-05-26T02:04:54Z","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/2605.25781/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Evaluating structured-information extraction from historical documents at scale requires high-precision ground-truth annotations, yet traditional manual labeling is expensive and fully automated pipelines built on large language models are prone to hallucination. We propose Double Triangle Annotation, a two-layer human-in-the-loop framework that leverages cross-model consensus to automate the majority of annotation work while ensuring high-precision outputs. In the first layer, two architecturally independent Multimodal Large Language Models annotate each document in parallel; when they agree,","authors_text":"Yi Ren","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T12:29:30Z","title":"Double Triangle Annotation: A Scalable Human-in-the-Loop Framework for High-Precision Historical Document Annotation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.25781","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":"sha256:597e8cfb7220229112d3de0f84f97a9a732c96daab1417e58962a599f51c0df5","target":"record","created_at":"2026-05-26T02:04:54Z","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":"cacdf54b67652ee7006d3cb6b82e46fc7d199a5a52ed0b6cc8d6c583f8ec30e9","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-25T12:29:30Z","title_canon_sha256":"3634708ab3f55a27bc772222042ce9e9fec2b780b6fad624e5b904ed989ab679"},"schema_version":"1.0","source":{"id":"2605.25781","kind":"arxiv","version":1}},"canonical_sha256":"7a9669f9a47fecfcf83d661feca144ac664135aee40c6776e9b40a3df851f526","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a9669f9a47fecfcf83d661feca144ac664135aee40c6776e9b40a3df851f526","first_computed_at":"2026-05-26T02:04:54.362958Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-26T02:04:54.362958Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G/a4LCK9xxPVdlvdeGOZH8wEYQKCjHnuz5Ux/7IzVLTDvXhfWFlCR4TBzi7ajXTGKlZxkxB22UBFymJ1ZiLpDg==","signature_status":"signed_v1","signed_at":"2026-05-26T02:04:54.363443Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.25781","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:597e8cfb7220229112d3de0f84f97a9a732c96daab1417e58962a599f51c0df5","sha256:2772b4b9b48320232226df0c91b282c3a2ddf28c68c85028000f088146c135d5"],"state_sha256":"f97ec08a11cf93abfd355d86207418f728d5d2c0697950d68083d4d3f09aafa4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sqrAI4X5DL/agxFcAmddyP4HcxOLsG9MqGv5JiONu0mKAoiSKfKMBnrAwlqxtYPCrVupANeK9C2OtZCiF7gwBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T20:55:02.333231Z","bundle_sha256":"b85702f09bcd13d4f22fb7c818dffc864d6265630f9141a1eada1ddb50624096"}}