{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:KPEEV5GO4SOIAQL67NRZGT5LN7","short_pith_number":"pith:KPEEV5GO","canonical_record":{"source":{"id":"2605.21712","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T20:14:55Z","cross_cats_sorted":[],"title_canon_sha256":"373245e44e02208ed36141a254b97aeb3e359ef62cf96c456f5de21f1024b402","abstract_canon_sha256":"bda43bac7d8289cb6b6bdc268e8db96ba0d3533f32aeb8f2e030db674faaa759"},"schema_version":"1.0"},"canonical_sha256":"53c84af4cee49c80417efb63934fab6fda865dd45f751b4e5a2759bcc4d271a7","source":{"kind":"arxiv","id":"2605.21712","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.21712","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"arxiv_version","alias_value":"2605.21712v1","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.21712","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_12","alias_value":"KPEEV5GO4SOI","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_16","alias_value":"KPEEV5GO4SOIAQL6","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_8","alias_value":"KPEEV5GO","created_at":"2026-05-22T01:03:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:KPEEV5GO4SOIAQL67NRZGT5LN7","target":"record","payload":{"canonical_record":{"source":{"id":"2605.21712","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T20:14:55Z","cross_cats_sorted":[],"title_canon_sha256":"373245e44e02208ed36141a254b97aeb3e359ef62cf96c456f5de21f1024b402","abstract_canon_sha256":"bda43bac7d8289cb6b6bdc268e8db96ba0d3533f32aeb8f2e030db674faaa759"},"schema_version":"1.0"},"canonical_sha256":"53c84af4cee49c80417efb63934fab6fda865dd45f751b4e5a2759bcc4d271a7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:03:28.979034Z","signature_b64":"w5ly6S5fir/3FLUx8po0xkz6BgRjEHZvL69aS4Qm7KPAjVZpDZx311srkUcKDDvYuCtOfQKEX83kwxQ9LtVOAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"53c84af4cee49c80417efb63934fab6fda865dd45f751b4e5a2759bcc4d271a7","last_reissued_at":"2026-05-22T01:03:28.978537Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:03:28.978537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.21712","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":"2026-05-22T01:03:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ibqwS+LfNqzoC1cyiVOK1CbbMB86pbYTcMylaP0GTzqeNp0gqiMTeqIoMMiqV6dUNnX4d3Y5dD7/vZG6DCfsCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T16:00:57.630803Z"},"content_sha256":"50b49ec2013d7bca41ab237e2a7517aff21abc2137bcb76ef3ab3c27f16eda25","schema_version":"1.0","event_id":"sha256:50b49ec2013d7bca41ab237e2a7517aff21abc2137bcb76ef3ab3c27f16eda25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:KPEEV5GO4SOIAQL67NRZGT5LN7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Eric J. Gonzales, Mahdi Azhdari","submitted_at":"2026-05-20T20:14:55Z","abstract_excerpt":"Transportation safety analysis requires integrating crash records, roadway attributes, and geospatial data through GIS-based workflows, but access remains uneven across agencies and community stakeholders. Technical prerequisites create a gap between analytical tools central to safety planning and the practitioners able to use them. Local agencies, school committees, and residents may have safety concerns but limited capacity to retrieve, filter, map, and analyze relevant data. Generative AI offers a way to narrow this divide, but its public-sector use raises questions about reliability, repro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.21712","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/2605.21712/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":"2026-05-22T01:03:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"STPG2mLJBJVeQyMDCBw31h12QEcmz0KtALzsueT5+F3YXKwjcMJFhBWAfn9hTrEM0WdR8ikTv7Fu3ivgEfSfCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-10T16:00:57.631578Z"},"content_sha256":"957d7a140015f9b0920eb25daeb4a6d28fc09ea31d518177ab362e5f40dd8b34","schema_version":"1.0","event_id":"sha256:957d7a140015f9b0920eb25daeb4a6d28fc09ea31d518177ab362e5f40dd8b34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/bundle.json","state_url":"https://pith.science/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/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":"2026-06-10T16:00:57Z","links":{"resolver":"https://pith.science/pith/KPEEV5GO4SOIAQL67NRZGT5LN7","bundle":"https://pith.science/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/bundle.json","state":"https://pith.science/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KPEEV5GO4SOIAQL67NRZGT5LN7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KPEEV5GO4SOIAQL67NRZGT5LN7","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":"bda43bac7d8289cb6b6bdc268e8db96ba0d3533f32aeb8f2e030db674faaa759","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T20:14:55Z","title_canon_sha256":"373245e44e02208ed36141a254b97aeb3e359ef62cf96c456f5de21f1024b402"},"schema_version":"1.0","source":{"id":"2605.21712","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.21712","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"arxiv_version","alias_value":"2605.21712v1","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.21712","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_12","alias_value":"KPEEV5GO4SOI","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_16","alias_value":"KPEEV5GO4SOIAQL6","created_at":"2026-05-22T01:03:28Z"},{"alias_kind":"pith_short_8","alias_value":"KPEEV5GO","created_at":"2026-05-22T01:03:28Z"}],"graph_snapshots":[{"event_id":"sha256:957d7a140015f9b0920eb25daeb4a6d28fc09ea31d518177ab362e5f40dd8b34","target":"graph","created_at":"2026-05-22T01:03:28Z","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/2605.21712/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transportation safety analysis requires integrating crash records, roadway attributes, and geospatial data through GIS-based workflows, but access remains uneven across agencies and community stakeholders. Technical prerequisites create a gap between analytical tools central to safety planning and the practitioners able to use them. Local agencies, school committees, and residents may have safety concerns but limited capacity to retrieve, filter, map, and analyze relevant data. Generative AI offers a way to narrow this divide, but its public-sector use raises questions about reliability, repro","authors_text":"Eric J. Gonzales, Mahdi Azhdari","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T20:14:55Z","title":"Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.21712","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":"sha256:50b49ec2013d7bca41ab237e2a7517aff21abc2137bcb76ef3ab3c27f16eda25","target":"record","created_at":"2026-05-22T01:03:28Z","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":"bda43bac7d8289cb6b6bdc268e8db96ba0d3533f32aeb8f2e030db674faaa759","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-20T20:14:55Z","title_canon_sha256":"373245e44e02208ed36141a254b97aeb3e359ef62cf96c456f5de21f1024b402"},"schema_version":"1.0","source":{"id":"2605.21712","kind":"arxiv","version":1}},"canonical_sha256":"53c84af4cee49c80417efb63934fab6fda865dd45f751b4e5a2759bcc4d271a7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"53c84af4cee49c80417efb63934fab6fda865dd45f751b4e5a2759bcc4d271a7","first_computed_at":"2026-05-22T01:03:28.978537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T01:03:28.978537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"w5ly6S5fir/3FLUx8po0xkz6BgRjEHZvL69aS4Qm7KPAjVZpDZx311srkUcKDDvYuCtOfQKEX83kwxQ9LtVOAg==","signature_status":"signed_v1","signed_at":"2026-05-22T01:03:28.979034Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.21712","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:50b49ec2013d7bca41ab237e2a7517aff21abc2137bcb76ef3ab3c27f16eda25","sha256:957d7a140015f9b0920eb25daeb4a6d28fc09ea31d518177ab362e5f40dd8b34"],"state_sha256":"4540deb184e88d745580c5238d0d6f308b3105e27b1dce7f18163e365556897c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zkm0Ym3O65+sXustN0n0hTQ+/N5jIPGIsn3BYMhe2mLsBHwiMnzApZ5EhFUtsoiwdhlQrYgRqngOTM3I3hNdAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-10T16:00:57.636301Z","bundle_sha256":"364b8aa745b5cfee6363bcfb03b4e850d8127f6743c7fe3cfbc6b8f2675c05eb"}}