{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:CK6TW5WYEXNYSC6PFTKXWIXMGY","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":"e542bb2944362864962fc22ac61170e439ba771d855dc2e822c2b1d180794f87","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-06T16:05:26Z","title_canon_sha256":"e7700541143b8436c580a30c203e1afb6050b0bc5053f5ce03d0961e9cb74a9e"},"schema_version":"1.0","source":{"id":"2607.05259","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.05259","created_at":"2026-07-07T03:19:21Z"},{"alias_kind":"arxiv_version","alias_value":"2607.05259v1","created_at":"2026-07-07T03:19:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05259","created_at":"2026-07-07T03:19:21Z"},{"alias_kind":"pith_short_12","alias_value":"CK6TW5WYEXNY","created_at":"2026-07-07T03:19:21Z"},{"alias_kind":"pith_short_16","alias_value":"CK6TW5WYEXNYSC6P","created_at":"2026-07-07T03:19:21Z"},{"alias_kind":"pith_short_8","alias_value":"CK6TW5WY","created_at":"2026-07-07T03:19:21Z"}],"graph_snapshots":[{"event_id":"sha256:8dee6f49430c5a1a356265215085c493b9fc96a240c7c770fa4e00ecc2672b9e","target":"graph","created_at":"2026-07-07T03:19:21Z","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/2607.05259/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications. In high-resource languages, this has been extended a step further, and instead of predicting sentiment at the sentence level, models have been developed to detect more fine-grained sentiments at aspect level. However, in order to conduct this fine-grained Aspect-based Sentiment Analysis (ABSA), datasets annotated with aspects and sentiments toward the said aspects is required. Such datasets are lacking for low-resources l","authors_text":"Adithya Galwatta, Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-06T16:05:26Z","title":"SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05259","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":"sha256:77996cbe759e66bfdee60c3df7317a47212097fbdd29044b555b7b3e371c6224","target":"record","created_at":"2026-07-07T03:19:21Z","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":"e542bb2944362864962fc22ac61170e439ba771d855dc2e822c2b1d180794f87","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-06T16:05:26Z","title_canon_sha256":"e7700541143b8436c580a30c203e1afb6050b0bc5053f5ce03d0961e9cb74a9e"},"schema_version":"1.0","source":{"id":"2607.05259","kind":"arxiv","version":1}},"canonical_sha256":"12bd3b76d825db890bcf2cd57b22ec36375e3fba08d6f2cd607df1d436194d93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"12bd3b76d825db890bcf2cd57b22ec36375e3fba08d6f2cd607df1d436194d93","first_computed_at":"2026-07-07T03:19:21.310591Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T03:19:21.310591Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hfyQX99f2pEIPDLjI8s+wctX59UywbwOmsif4cwAjaOVcgMevhUJ5OlCeTT0hayACx+CQfrtdazFS2y9OuEcBA==","signature_status":"signed_v1","signed_at":"2026-07-07T03:19:21.311036Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.05259","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:77996cbe759e66bfdee60c3df7317a47212097fbdd29044b555b7b3e371c6224","sha256:8dee6f49430c5a1a356265215085c493b9fc96a240c7c770fa4e00ecc2672b9e"],"state_sha256":"9509b6dd9444f66ba206b5a78be896ab95f591799f7ad772c9a337fcc7260032"}