{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:5YNI7TKIG65V6H267YRI4AF4FR","short_pith_number":"pith:5YNI7TKI","schema_version":"1.0","canonical_sha256":"ee1a8fcd4837bb5f1f5efe228e00bc2c5dc0e76069b7b71afa843d9ecaa655b7","source":{"kind":"arxiv","id":"2407.06041","version":1},"attestation_state":"computed","paper":{"title":"MST5 -- Multilingual Question Answering over Knowledge Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Axel-Cyrille Ngonga Ngomo, Daniel Vollmers, Diego Moussallem, Hamada Zahera, Mengshi Ma, Nikit Srivastava","submitted_at":"2024-07-08T15:37:51Z","abstract_excerpt":"Knowledge Graph Question Answering (KGQA) simplifies querying vast amounts of knowledge stored in a graph-based model using natural language. However, the research has largely concentrated on English, putting non-English speakers at a disadvantage. Meanwhile, existing multilingual KGQA systems face challenges in achieving performance comparable to English systems, highlighting the difficulty of generating SPARQL queries from diverse languages. In this research, we propose a simplified approach to enhance multilingual KGQA systems by incorporating linguistic context and entity information direc"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2407.06041","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-07-08T15:37:51Z","cross_cats_sorted":[],"title_canon_sha256":"c30959771154c0d59eda5568051763e1bb8d91ce482ca2f673cf8d67397f31e6","abstract_canon_sha256":"585efe66f81b1a71aa3eebf1e25988521056d4f78d4670c805999ac90593cc26"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:41:22.635296Z","signature_b64":"Hua94GcKBvs8jgWgL5dDtH1jqHcDSr7DU9AC9mf7Qz1/ZDdFLe5QGqKE3Z5uucG3iZdFrBl1xKauR80Y3bIxCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ee1a8fcd4837bb5f1f5efe228e00bc2c5dc0e76069b7b71afa843d9ecaa655b7","last_reissued_at":"2026-07-05T08:41:22.634850Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:41:22.634850Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"MST5 -- Multilingual Question Answering over Knowledge Graphs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Axel-Cyrille Ngonga Ngomo, Daniel Vollmers, Diego Moussallem, Hamada Zahera, Mengshi Ma, Nikit Srivastava","submitted_at":"2024-07-08T15:37:51Z","abstract_excerpt":"Knowledge Graph Question Answering (KGQA) simplifies querying vast amounts of knowledge stored in a graph-based model using natural language. However, the research has largely concentrated on English, putting non-English speakers at a disadvantage. Meanwhile, existing multilingual KGQA systems face challenges in achieving performance comparable to English systems, highlighting the difficulty of generating SPARQL queries from diverse languages. In this research, we propose a simplified approach to enhance multilingual KGQA systems by incorporating linguistic context and entity information direc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.06041","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/2407.06041/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2407.06041","created_at":"2026-07-05T08:41:22.634909+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.06041v1","created_at":"2026-07-05T08:41:22.634909+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.06041","created_at":"2026-07-05T08:41:22.634909+00:00"},{"alias_kind":"pith_short_12","alias_value":"5YNI7TKIG65V","created_at":"2026-07-05T08:41:22.634909+00:00"},{"alias_kind":"pith_short_16","alias_value":"5YNI7TKIG65V6H26","created_at":"2026-07-05T08:41:22.634909+00:00"},{"alias_kind":"pith_short_8","alias_value":"5YNI7TKI","created_at":"2026-07-05T08:41:22.634909+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR","json":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR.json","graph_json":"https://pith.science/api/pith-number/5YNI7TKIG65V6H267YRI4AF4FR/graph.json","events_json":"https://pith.science/api/pith-number/5YNI7TKIG65V6H267YRI4AF4FR/events.json","paper":"https://pith.science/paper/5YNI7TKI"},"agent_actions":{"view_html":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR","download_json":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR.json","view_paper":"https://pith.science/paper/5YNI7TKI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.06041&json=true","fetch_graph":"https://pith.science/api/pith-number/5YNI7TKIG65V6H267YRI4AF4FR/graph.json","fetch_events":"https://pith.science/api/pith-number/5YNI7TKIG65V6H267YRI4AF4FR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR/action/storage_attestation","attest_author":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR/action/author_attestation","sign_citation":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR/action/citation_signature","submit_replication":"https://pith.science/pith/5YNI7TKIG65V6H267YRI4AF4FR/action/replication_record"}},"created_at":"2026-07-05T08:41:22.634909+00:00","updated_at":"2026-07-05T08:41:22.634909+00:00"}