{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:G334577FIYSGK6UIJYYGLIB2R2","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":"f6d2a86b4b8100afae1ca4c4ccaf3e2f4ee821558619fe16c96808188bc304dd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-13T15:20:51Z","title_canon_sha256":"7c5f48e5e5185e69417a37089ea83c52796cd82f3edb4c20a7ef175184a29b0e"},"schema_version":"1.0","source":{"id":"2607.11683","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.11683","created_at":"2026-07-14T02:22:18Z"},{"alias_kind":"arxiv_version","alias_value":"2607.11683v1","created_at":"2026-07-14T02:22:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.11683","created_at":"2026-07-14T02:22:18Z"},{"alias_kind":"pith_short_12","alias_value":"G334577FIYSG","created_at":"2026-07-14T02:22:18Z"},{"alias_kind":"pith_short_16","alias_value":"G334577FIYSGK6UI","created_at":"2026-07-14T02:22:18Z"},{"alias_kind":"pith_short_8","alias_value":"G334577F","created_at":"2026-07-14T02:22:18Z"}],"graph_snapshots":[{"event_id":"sha256:4df9b2173694b49266dd2d37b828bd62d876fcd38002e47a36739685cc3e9431","target":"graph","created_at":"2026-07-14T02:22:18Z","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/2607.11683/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph retrieval-augmented generation (GraphRAG) enhances large language models with structured knowledge, yet existing systems construct knowledge graphs in a single extraction pass, producing noisy entities and brittle retrieval. RAGU, an open-source modular GraphRAG engine, addresses this by separating extraction from consolidation: entities and relations pass through two-stage typed extraction, DBSCAN-backed deduplication, LLM summarization, and Leiden community detection. A key insight motivates a compact extractor: the skills an in-pipeline LLM needs - comprehension, extraction, reasoning","authors_text":"Ivan Bondarenko, Matvey Solovyov, Mikhail Komarov, Nikolay O. Nikitin, Oleg Sedukhin, Roman Shuvalov, Stanislav Shtuka, Yana Dementyeva","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-13T15:20:51Z","title":"RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.11683","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":"sha256:0710f06d6fd5885c2f22cbdf1fe8d7e517746d20aa24e7c11b3861eadd8bb2d5","target":"record","created_at":"2026-07-14T02:22:18Z","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":"f6d2a86b4b8100afae1ca4c4ccaf3e2f4ee821558619fe16c96808188bc304dd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-13T15:20:51Z","title_canon_sha256":"7c5f48e5e5185e69417a37089ea83c52796cd82f3edb4c20a7ef175184a29b0e"},"schema_version":"1.0","source":{"id":"2607.11683","kind":"arxiv","version":1}},"canonical_sha256":"36f7ceffe54624657a884e3065a03a8eb78769a3f810d5d869c383e791579f1a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36f7ceffe54624657a884e3065a03a8eb78769a3f810d5d869c383e791579f1a","first_computed_at":"2026-07-14T02:22:18.938516Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T02:22:18.938516Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LNgh/loaIbeBTDqcM3AAZaPevVuqfLVVFo3gzOWx3SUbnv/T/y6zz2MYuL/R2LR1nXvGotU4jJkeAAvvPgl9Bw==","signature_status":"signed_v1","signed_at":"2026-07-14T02:22:18.939324Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.11683","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0710f06d6fd5885c2f22cbdf1fe8d7e517746d20aa24e7c11b3861eadd8bb2d5","sha256:4df9b2173694b49266dd2d37b828bd62d876fcd38002e47a36739685cc3e9431"],"state_sha256":"18d71c57e1f51a500f95351f9e61b6bf69adb3c819e6342b4c25b5f3f693f662"}