{"id":"https://openalex.org/W3046423960","doi":"https://doi.org/10.18653/v1/d19-5804","title":"Improving Subject-Area Question Answering with External Knowledge","display_name":"Improving Subject-Area Question Answering with External Knowledge","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W3046423960","doi":"https://doi.org/10.18653/v1/d19-5804","mag":"3046423960"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d19-5804","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5804","pdf_url":"https://www.aclweb.org/anthology/D19-5804.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D19-5804.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022703491","display_name":"Xiaoman Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiaoman Pan","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053739372","display_name":"Kai Sun","orcid":"https://orcid.org/0000-0003-2281-5051"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Sun","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101834699","display_name":"Dian Yu","orcid":"https://orcid.org/0000-0002-8583-8931"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dian Yu","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088339142","display_name":"Jianshu Chen","orcid":"https://orcid.org/0000-0001-8216-2756"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianshu Chen","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103178893","display_name":"Heng Ji","orcid":"https://orcid.org/0000-0002-7954-7994"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng Ji","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Champaign, IL, USA"],"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Champaign, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070511738","display_name":"Claire Cardie","orcid":"https://orcid.org/0000-0002-2061-6094"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Claire Cardie","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034476404","display_name":"Dong Yu","orcid":"https://orcid.org/0000-0003-0520-6844"},"institutions":[{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dong Yu","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA, USA"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210108985"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5022703491"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":4.7606,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.96038447,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"27","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9979000091552734,"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":0.9937000274658203,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.8274961113929749},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8236937522888184},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.7450643181800842},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5620098114013672},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.5543632507324219},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5533514022827148},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5273842811584473},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5034708380699158},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.46411070227622986},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.4516368508338928},{"id":"https://openalex.org/keywords/subject-matter-expert","display_name":"Subject-matter expert","score":0.42850568890571594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37712371349334717},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.33964642882347107},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.327975332736969},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.2182278037071228}],"concepts":[{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.8274961113929749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8236937522888184},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.7450643181800842},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5620098114013672},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.5543632507324219},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5533514022827148},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5273842811584473},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5034708380699158},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.46411070227622986},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.4516368508338928},{"id":"https://openalex.org/C105002631","wikidata":"https://www.wikidata.org/wiki/Q4833645","display_name":"Subject-matter expert","level":3,"score":0.42850568890571594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37712371349334717},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.33964642882347107},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.327975332736969},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2182278037071228},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C58328972","wikidata":"https://www.wikidata.org/wiki/Q184609","display_name":"Expert system","level":2,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d19-5804","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5804","pdf_url":"https://www.aclweb.org/anthology/D19-5804.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d19-5804","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d19-5804","pdf_url":"https://www.aclweb.org/anthology/D19-5804.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd Workshop on Machine Reading for Question Answering","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3046423960.pdf","grobid_xml":"https://content.openalex.org/works/W3046423960.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W2007018602","https://openalex.org/W2053468515","https://openalex.org/W2059035806","https://openalex.org/W2123442489","https://openalex.org/W2143017621","https://openalex.org/W2252077675","https://openalex.org/W2293174806","https://openalex.org/W2460591548","https://openalex.org/W2547185913","https://openalex.org/W2561529111","https://openalex.org/W2606964149","https://openalex.org/W2608309533","https://openalex.org/W2609826708","https://openalex.org/W2734823783","https://openalex.org/W2741412196","https://openalex.org/W2753329127","https://openalex.org/W2773352682","https://openalex.org/W2788496822","https://openalex.org/W2788705621","https://openalex.org/W2790767126","https://openalex.org/W2794325560","https://openalex.org/W2799042618","https://openalex.org/W2799081691","https://openalex.org/W2805387248","https://openalex.org/W2889453388","https://openalex.org/W2889729765","https://openalex.org/W2890894339","https://openalex.org/W2896457183","https://openalex.org/W2912817604","https://openalex.org/W2912924812","https://openalex.org/W2945329331","https://openalex.org/W2949594791","https://openalex.org/W2951534261","https://openalex.org/W2951922096","https://openalex.org/W2953038430","https://openalex.org/W2953320089","https://openalex.org/W2962829834","https://openalex.org/W2962865973","https://openalex.org/W2962985038","https://openalex.org/W2963123047","https://openalex.org/W2963339397","https://openalex.org/W2963341956","https://openalex.org/W2963371565","https://openalex.org/W2963547127","https://openalex.org/W2963564796","https://openalex.org/W2963748441","https://openalex.org/W2963895422","https://openalex.org/W2963997623","https://openalex.org/W2964222271","https://openalex.org/W2977745385","https://openalex.org/W2978990807","https://openalex.org/W3121694563","https://openalex.org/W4289360545","https://openalex.org/W4294329082","https://openalex.org/W4295253143"],"related_works":["https://openalex.org/W1583422155","https://openalex.org/W2086580554","https://openalex.org/W4296913697","https://openalex.org/W2078297485","https://openalex.org/W2158321484","https://openalex.org/W2787275075","https://openalex.org/W2295405411","https://openalex.org/W9567558","https://openalex.org/W3213252596","https://openalex.org/W1649619740"],"abstract_inverted_index":{"We":[0],"focus":[1],"on":[2],"multiple-choice":[3],"question":[4,75],"answering":[5],"(QA)":[6],"tasks":[7],"in":[8,73,80],"subject":[9],"areas":[10],"such":[11],"as":[12],"science,":[13],"where":[14],"we":[15,33],"require":[16],"both":[17],"broad":[18],"background":[19],"knowledge":[20,45],"and":[21,76],"the":[22,25,52,74,84,89],"facts":[23],"from":[24,62],"given":[26],"subject-area":[27,47,54,98],"reference":[28,55],"corpus.":[29],"In":[30],"this":[31],"work,":[32],"explore":[34],"simple":[35],"yet":[36],"effective":[37],"methods":[38],"for":[39,46],"exploiting":[40],"two":[41],"sources":[42],"of":[43,91],"external":[44],"QA.":[48],"The":[49],"first":[50],"enriches":[51],"original":[53],"corpus":[56],"with":[57],"relevant":[58],"text":[59],"snippets":[60],"extracted":[61],"an":[63],"open-domain":[64],"resource":[65],"(i.e.,":[66],"Wikipedia)":[67],"that":[68],"cover":[69],"potentially":[70],"ambiguous":[71],"concepts":[72],"answer":[77],"options.":[78],"As":[79],"other":[81],"QA":[82],"research,":[83],"second":[85],"method":[86],"simply":[87],"increases":[88],"amount":[90],"training":[92],"data":[93],"by":[94],"appending":[95],"additional":[96],"indomain":[97],"instances.":[99]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":16},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":6}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}