{"id":"https://openalex.org/W7162489506","doi":"https://doi.org/10.48550/arxiv.2605.27164","title":"Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering","display_name":"Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering","publication_year":2026,"publication_date":"2026-05-26","ids":{"openalex":"https://openalex.org/W7162489506","doi":"https://doi.org/10.48550/arxiv.2605.27164"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.27164","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.27164","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099111514","display_name":"Mateusz Czy\u017cnikiewicz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Czy\u017cnikiewicz, Mateusz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137139273","display_name":"Ryszard Tuora","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tuora, Ryszard","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132597111","display_name":"Adam Kozakiewicz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kozakiewicz, Adam","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137188881","display_name":"Tomasz Zi\u0119tkiewicz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zi\u0119tkiewicz, Tomasz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132647093","display_name":"Mateusz Gali\u0144ski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gali\u0144ski, Mateusz","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137146059","display_name":"Micha\u0142 Godziszewski","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Godziszewski, Micha\u0142","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137157096","display_name":"Micha\u0142 Karpowicz","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karpowicz, Micha\u0142","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5137128369","display_name":"Timothy Hospedales","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hospedales, Timothy","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5027858626","display_name":"Cristina Cornelio","orcid":"https://orcid.org/0000-0001-5284-6487"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cornelio, Cristina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":9,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8575000166893005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.8575000166893005,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.04780000075697899,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.046799998730421066,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7174999713897705},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.48089998960494995},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4659999907016754},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4345000088214874},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.41679999232292175},{"id":"https://openalex.org/keywords/document-retrieval","display_name":"Document retrieval","score":0.3433000147342682},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.33079999685287476},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3262999951839447}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8151999711990356},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7174999713897705},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.6116999983787537},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4659999907016754},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4345000088214874},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3813000023365021},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3725999891757965},{"id":"https://openalex.org/C161156560","wikidata":"https://www.wikidata.org/wiki/Q1638872","display_name":"Document retrieval","level":2,"score":0.3433000147342682},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.33079999685287476},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3262999951839447},{"id":"https://openalex.org/C69075417","wikidata":"https://www.wikidata.org/wiki/Q515701","display_name":"Linked data","level":3,"score":0.3222000002861023},{"id":"https://openalex.org/C2778816267","wikidata":"https://www.wikidata.org/wiki/Q21015578","display_name":"Semantic query","level":4,"score":0.2964000105857849},{"id":"https://openalex.org/C44083865","wikidata":"https://www.wikidata.org/wiki/Q3853443","display_name":"Mean reciprocal rank","level":2,"score":0.2791999876499176},{"id":"https://openalex.org/C86034646","wikidata":"https://www.wikidata.org/wiki/Q474311","display_name":"Semantic gap","level":4,"score":0.2750000059604645},{"id":"https://openalex.org/C120567893","wikidata":"https://www.wikidata.org/wiki/Q1582085","display_name":"Knowledge extraction","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2129575","wikidata":"https://www.wikidata.org/wiki/Q54837","display_name":"Semantic Web","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C99016210","wikidata":"https://www.wikidata.org/wiki/Q5488129","display_name":"Query expansion","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C176225458","wikidata":"https://www.wikidata.org/wiki/Q595971","display_name":"Graph database","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C192028432","wikidata":"https://www.wikidata.org/wiki/Q845739","display_name":"Query language","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C161301231","wikidata":"https://www.wikidata.org/wiki/Q3478658","display_name":"Knowledge representation and reasoning","level":2,"score":0.26649999618530273},{"id":"https://openalex.org/C143271835","wikidata":"https://www.wikidata.org/wiki/Q254515","display_name":"Similitude","level":2,"score":0.26260000467300415}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.27164","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.27164","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.27164","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Retrieval-Augmented":[0],"Generation":[1],"(RAG)":[2],"systems":[3],"for":[4,21,82,90,106],"question":[5,151],"answering":[6,33],"typically":[7],"retrieve":[8],"evidence":[9],"by":[10],"semantic":[11,83,110],"similarity":[12],"between":[13],"the":[14],"query":[15],"and":[16,85,111,128,134,147,153],"document":[17],"chunks.":[18],"While":[19],"effective":[20],"unstructured":[22],"text,":[23],"this":[24,64],"approach":[25],"is":[26],"less":[27],"reliable":[28],"on":[29,58,98],"semi-structured":[30,125],"corpora":[31],"where":[32],"may":[34],"require":[35],"exact":[36],"filtering,":[37],"aggregation,":[38],"or":[39,108],"exhaustive":[40],"retrieval":[41,84],"over":[42,93],"structured":[43],"attributes":[44],"across":[45,150],"multiple":[46,104],"documents.":[47],"Symbolic":[48,87],"approaches":[49],"support":[50],"such":[51],"operations,":[52],"but":[53],"they":[54],"are":[55,155],"often":[56],"brittle":[57],"noisy":[59],"natural-language":[60],"corpora.":[61],"We":[62],"address":[63],"gap":[65],"with":[66,124],"DualGraph,":[67],"a":[68,78,86,117,120],"RAG":[69],"framework":[70],"that":[71,139],"represents":[72],"documents":[73,127],"through":[74],"two":[75,100],"complementary":[76],"views:":[77],"Textual":[79],"Knowledge":[80,88],"Graph":[81,89],"symbolic":[91,112],"querying":[92],"typed":[94],"subject--predicate--object":[95],"triples.":[96],"Building":[97],"these":[99],"components,":[101],"we":[102],"provide":[103],"strategies":[105],"selecting":[107],"combining":[109],"evidence.We":[113],"also":[114],"introduce":[115],"SpecsQA,":[116],"benchmark":[118],"from":[119],"commercial":[121],"shopping":[122],"website":[123],"product":[126],"manually":[129],"curated":[130],"questions":[131],"spanning":[132],"open-ended":[133],"specification-oriented":[135],"retrieval.":[136],"Experiments":[137],"show":[138],"DualGraph":[140],"consistently":[141],"outperforms":[142],"state-of-the-art":[143],"dense-retrieval,":[144],"GraphRAG,":[145],"symbolic,":[146],"table-oriented":[148],"baselines":[149],"types.Code":[152],"data":[154],"available":[156],"at":[157],"https://github.com/corneliocristina/DualGraphRAG.":[158]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-28T00:00:00"}