{"id":"https://openalex.org/W7164181771","doi":"https://doi.org/10.48550/arxiv.2606.10644","title":"Answer Set Programming for Egg Extraction and More","display_name":"Answer Set Programming for Egg Extraction and More","publication_year":2026,"publication_date":"2026-06-09","ids":{"openalex":"https://openalex.org/W7164181771","doi":"https://doi.org/10.48550/arxiv.2606.10644"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.10644","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10644","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.10644","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138343182","display_name":"Ziyi Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Ziyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5009639508","display_name":"Ilya Sergey","orcid":"https://orcid.org/0000-0003-4250-5392"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sergey, Ilya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.7332000136375427,"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/T11010","display_name":"Logic, Reasoning, and Knowledge","score":0.7332000136375427,"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/T10028","display_name":"Topic Modeling","score":0.04610000178217888,"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/T10215","display_name":"Semantic Web and Ontologies","score":0.04560000076889992,"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/answer-set-programming","display_name":"Answer set programming","score":0.9182999730110168},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.704200029373169},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.6261000037193298},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.3959999978542328},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.38960000872612},{"id":"https://openalex.org/keywords/yield","display_name":"Yield (engineering)","score":0.36959999799728394}],"concepts":[{"id":"https://openalex.org/C182620335","wikidata":"https://www.wikidata.org/wiki/Q2852531","display_name":"Answer set programming","level":3,"score":0.9182999730110168},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.704200029373169},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6355000138282776},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.6261000037193298},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43220001459121704},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.3959999978542328},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C134121241","wikidata":"https://www.wikidata.org/wiki/Q899301","display_name":"Yield (engineering)","level":2,"score":0.36959999799728394},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C2776608160","wikidata":"https://www.wikidata.org/wiki/Q4785462","display_name":"Natural (archaeology)","level":2,"score":0.35989999771118164},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31619998812675476},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C41045048","wikidata":"https://www.wikidata.org/wiki/Q202843","display_name":"Linear programming","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C184264201","wikidata":"https://www.wikidata.org/wiki/Q21199","display_name":"Natural number","level":2,"score":0.27730000019073486},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2655999958515167},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.10644","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10644","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.10644","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.10644","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Three":[0],"years":[1],"ago,":[2],"Philip":[3],"Zucker":[4],"posted":[5],"an":[6],"attempt":[7,35],"to":[8,53,78,101],"use":[9],"answer":[10],"set":[11],"programming":[12],"(ASP)":[13],"for":[14],"term":[15],"extraction":[16,84,93],"from":[17,130],"e-graphs":[18],"Although":[19],"the":[20,33,42,51,61,70,79,86,95,106,127],"task":[21,62],"is":[22,74,111],"NP-hard":[23],"and":[24,57,88],"ASP":[25,46,55,72,119],"offers":[26],"a":[27,102,113,121],"natural":[28],"modelling":[29],"of":[30,44,63,109],"e-graph":[31,64],"terms,":[32],"initial":[34,67],"did":[36],"not":[37],"yield":[38],"convincing":[39],"results.":[40],"From":[41],"aspect":[43],"practical":[45],"users,":[47],"we":[48],"first":[49],"pinpoint":[50],"way":[52],"make":[54],"work":[56,58],"well":[59],"on":[60,76,94],"extraction.":[65],"The":[66],"results":[68],"show":[69],"na\u00efve":[71],"encoding":[73],"comparable":[75],"efficiency":[77],"well-optimised":[80],"ILP-based":[81],"exact":[82],"DAG":[83],"in":[85],"extraction-gym,":[87],"find":[89],"several":[90],"extra":[91],"optimal":[92],"complex":[96],"instances.":[97],"This":[98],"leads":[99],"us":[100],"further":[103],"agenda:":[104],"with":[105],"\"better":[107,115],"together":[108],"egg+Datalog\",":[110],"there":[112],"better":[114],"together\"":[116],"by":[117],"having":[118],"as":[120],"more":[122],"powerful":[123],"Datalog?":[124],"We":[125],"discuss":[126],"potential":[128],"benefit":[129],"each":[131],"other.":[132]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-11T00:00:00"}
