{"id":"https://openalex.org/W2995238850","doi":"https://doi.org/10.1162/tacl_a_00305","title":"Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension","display_name":"Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension","publication_year":2020,"publication_date":"2020-03-31","ids":{"openalex":"https://openalex.org/W2995238850","doi":"https://doi.org/10.1162/tacl_a_00305","mag":"2995238850"},"language":"en","primary_location":{"id":"doi:10.1162/tacl_a_00305","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00305","pdf_url":null,"source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1162/tacl_a_00305","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","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","cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"cornell University","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/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]},{"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":["CN","US"],"is_corresponding":false,"raw_author_name":"Dian Yu","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA","[Tencent AI Lab]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA","institution_ids":["https://openalex.org/I4210108985"]},{"raw_affiliation_string":"[Tencent AI Lab]","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034476404","display_name":"Dong Yu","orcid":"https://orcid.org/0000-0003-0520-6844"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]},{"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":["CN","US"],"is_corresponding":false,"raw_author_name":"Dong Yu","raw_affiliation_strings":["Tencent AI Lab, Bellevue, WA","[Tencent AI Lab]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Bellevue, WA","institution_ids":["https://openalex.org/I4210108985"]},{"raw_affiliation_string":"[Tencent AI Lab]","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","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","cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"cornell University","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6713,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.76071327,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":"8","issue":null,"first_page":"141","last_page":"155"},"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":0.9998999834060669,"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/T13629","display_name":"Text Readability and Simplification","score":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.7869081497192383},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7637263536453247},{"id":"https://openalex.org/keywords/reading-comprehension","display_name":"Reading comprehension","score":0.6621001958847046},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6344579458236694},{"id":"https://openalex.org/keywords/comprehension","display_name":"Comprehension","score":0.6284670829772949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6077581644058228},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.5613986849784851},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.5392040610313416},{"id":"https://openalex.org/keywords/question-answering","display_name":"Question answering","score":0.4919845759868622},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.46382203698158264},{"id":"https://openalex.org/keywords/general-knowledge","display_name":"General knowledge","score":0.4490995705127716},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3279675841331482},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.21886464953422546},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.13354039192199707}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7869081497192383},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7637263536453247},{"id":"https://openalex.org/C2778780117","wikidata":"https://www.wikidata.org/wiki/Q3269423","display_name":"Reading comprehension","level":3,"score":0.6621001958847046},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6344579458236694},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.6284670829772949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6077581644058228},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.5613986849784851},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.5392040610313416},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.4919845759868622},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.46382203698158264},{"id":"https://openalex.org/C49929091","wikidata":"https://www.wikidata.org/wiki/Q1930471","display_name":"General knowledge","level":2,"score":0.4490995705127716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3279675841331482},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.21886464953422546},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.13354039192199707},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1162/tacl_a_00305","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00305","pdf_url":null,"source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1904.09679","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.09679","pdf_url":"https://arxiv.org/pdf/1904.09679","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2995238850","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1904.09679.pdf","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"pmh:oai:doaj.org/article:e7adaf31d22245b69b57df0fd57d7cfe","is_oa":true,"landing_page_url":"https://doaj.org/article/e7adaf31d22245b69b57df0fd57d7cfe","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Transactions of the Association for Computational Linguistics, Vol 8, Pp 141-155 (2020)","raw_type":"article"},{"id":"doi:10.48550/arxiv.1904.09679","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1904.09679","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":"Preprint"},{"id":"mag:3185680263","is_oa":false,"landing_page_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/tacl_a_00305","pdf_url":null,"source":{"id":"https://openalex.org/S4306420508","display_name":"Meeting of the Association for Computational Linguistics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":"Meeting of the Association for Computational Linguistics","raw_type":null}],"best_oa_location":{"id":"doi:10.1162/tacl_a_00305","is_oa":true,"landing_page_url":"https://doi.org/10.1162/tacl_a_00305","pdf_url":null,"source":{"id":"https://openalex.org/S2729999759","display_name":"Transactions of the Association for Computational Linguistics","issn_l":"2307-387X","issn":["2307-387X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transactions of the Association for Computational Linguistics","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8999999761581421,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W10398066","https://openalex.org/W1544827683","https://openalex.org/W1588242179","https://openalex.org/W1707739730","https://openalex.org/W2016045035","https://openalex.org/W2038721957","https://openalex.org/W2078288474","https://openalex.org/W2081484085","https://openalex.org/W2090243146","https://openalex.org/W2092527610","https://openalex.org/W2094811024","https://openalex.org/W2125436846","https://openalex.org/W2130947465","https://openalex.org/W2145778737","https://openalex.org/W2161915178","https://openalex.org/W2163908084","https://openalex.org/W2181863911","https://openalex.org/W2187938785","https://openalex.org/W2250491758","https://openalex.org/W2251872787","https://openalex.org/W2341790067","https://openalex.org/W2495998536","https://openalex.org/W2528904340","https://openalex.org/W2547185913","https://openalex.org/W2557764419","https://openalex.org/W2561222820","https://openalex.org/W2572223286","https://openalex.org/W2612431505","https://openalex.org/W2624677889","https://openalex.org/W2740001335","https://openalex.org/W2769934148","https://openalex.org/W2785919443","https://openalex.org/W2804897457","https://openalex.org/W2806055002","https://openalex.org/W2806081754","https://openalex.org/W2810519866","https://openalex.org/W2888302696","https://openalex.org/W2889048825","https://openalex.org/W2889641747","https://openalex.org/W2890894339","https://openalex.org/W2891737971","https://openalex.org/W2896457183","https://openalex.org/W2898662126","https://openalex.org/W2898695519","https://openalex.org/W2912904516","https://openalex.org/W2928107702","https://openalex.org/W2938830017","https://openalex.org/W2946659172","https://openalex.org/W2949884065","https://openalex.org/W2951534261","https://openalex.org/W2962934410","https://openalex.org/W2962990932","https://openalex.org/W2963270153","https://openalex.org/W2963323070","https://openalex.org/W2963744614","https://openalex.org/W2963748441","https://openalex.org/W2963866616","https://openalex.org/W2963956494","https://openalex.org/W2963963993","https://openalex.org/W2963983586","https://openalex.org/W2964207259","https://openalex.org/W2964222271","https://openalex.org/W2964223283","https://openalex.org/W2964246695","https://openalex.org/W2964267515","https://openalex.org/W2970092972","https://openalex.org/W3106031450","https://openalex.org/W3210120707"],"related_works":["https://openalex.org/W2936074642","https://openalex.org/W3185680263","https://openalex.org/W2951627291","https://openalex.org/W2970597249","https://openalex.org/W2963341956","https://openalex.org/W2125436846","https://openalex.org/W2987215000","https://openalex.org/W2890565896","https://openalex.org/W3088056511","https://openalex.org/W2971740165","https://openalex.org/W2945392868","https://openalex.org/W2994636820","https://openalex.org/W2962979564","https://openalex.org/W2779681640","https://openalex.org/W3178406120","https://openalex.org/W2963829073","https://openalex.org/W2949615363","https://openalex.org/W3110359711","https://openalex.org/W3083239953","https://openalex.org/W2411480514"],"abstract_inverted_index":{"Machine":[0],"reading":[1,27],"comprehension":[2],"tasks":[3],"require":[4,105],"a":[5,56,88,163,178],"machine":[6,26],"reader":[7],"to":[8,12,133,137,165,168,175],"answer":[9],"questions":[10,49,144],"relevant":[11,122],"the":[13,21,60,93,111,151],"given":[14,179],"document.":[15],"In":[16],"this":[17],"paper,":[18],"we":[19,155],"present":[20,55,134],"first":[22],"free-form":[23,48],"multiple-Choice":[24],"Chinese":[25],"Comprehension":[28],"dataset":[29],"(C":[30],"3":[31,132,159,186],"),":[32],"containing":[33],"13,369":[34],"documents":[35],"(dialogues":[36],"or":[37,181],"more":[38],"formally":[39],"written":[40,180],"mixed-genre":[41],"texts)":[42],"and":[43,66,78,82,98,116,149,154],"their":[44],"associated":[45],"19,577":[46],"multiple-choice":[47],"collected":[50],"from":[51],"Chinese-as-a-second-language":[52],"examinations.":[53],"We":[54,75,108,129],"comprehensive":[57],"analysis":[58],"of":[59,113,143,172],"prior":[61,106,173],"knowledge":[62,147,174],"(i.e.,":[63],"linguistic,":[64],"domain-specific,":[65],"general":[67],"world":[68],"knowledge)":[69],"needed":[70],"for":[71,124],"these":[72],"real-world":[73],"problems.":[74],"implement":[76],"rule-based":[77],"popular":[79],"neural":[80],"methods":[81],"find":[83],"that":[84,104,157],"there":[85],"is":[86,187],"still":[87],"significant":[89],"performance":[90],"gap":[91],"between":[92],"best":[94],"performing":[95],"model":[96,127],"(68.5%)":[97],"human":[99],"readers":[100],"(96.0%),":[101],"especiallyon":[102],"problems":[103],"knowledge.":[107],"further":[109],"study":[110,166],"effects":[112],"distractor":[114],"plausibility":[115],"data":[117],"augmentation":[118],"based":[119],"on":[120,126],"translated":[121],"datasets":[123],"English":[125],"performance.":[128],"expect":[130],"C":[131,158,185],"great":[135],"challenges":[136],"existing":[138],"systems":[139],"as":[140,162],"answering":[141],"86.8%":[142],"requires":[145],"both":[146],"within":[148],"beyond":[150],"accompanying":[152],"document,":[153],"hope":[156],"can":[160],"serve":[161],"platform":[164],"how":[167],"leverage":[169],"various":[170],"kinds":[171],"better":[176],"understand":[177],"orally":[182],"oriented":[183],"text.":[184],"available":[188],"at":[189],"https://dataset.org/c3/":[190],".":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
