{"id":"https://openalex.org/W2903761862","doi":"https://doi.org/10.1017/s135132491800044x","title":"InferPortOIE: A Portuguese Open Information Extraction system with inferences","display_name":"InferPortOIE: A Portuguese Open Information Extraction system with inferences","publication_year":2018,"publication_date":"2018-12-14","ids":{"openalex":"https://openalex.org/W2903761862","doi":"https://doi.org/10.1017/s135132491800044x","mag":"2903761862"},"language":"en","primary_location":{"id":"doi:10.1017/s135132491800044x","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s135132491800044x","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084382706","display_name":"Cleiton Fernando Lima Sena","orcid":null},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Cleiton Fernando Lima Sena","raw_affiliation_strings":["Formalisms and Semantic Applications Research Group (FORMAS), LaSiD/DCC/IME\u2014Federal University of Bahia (UFBA), Av. Adhemar de Barros, s/n, Campus de Ondina, Salvador, Bahia, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Formalisms and Semantic Applications Research Group (FORMAS), LaSiD/DCC/IME\u2014Federal University of Bahia (UFBA), Av. Adhemar de Barros, s/n, Campus de Ondina, Salvador, Bahia, Brazil","institution_ids":["https://openalex.org/I126158947"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002539501","display_name":"Daniela Barreiro Claro","orcid":"https://orcid.org/0000-0001-8586-1042"},"institutions":[{"id":"https://openalex.org/I126158947","display_name":"Universidade Federal da Bahia","ror":"https://ror.org/03k3p7647","country_code":"BR","type":"education","lineage":["https://openalex.org/I126158947"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Daniela Barreiro Claro","raw_affiliation_strings":["Formalisms and Semantic Applications Research Group (FORMAS), LaSiD/DCC/IME\u2014Federal University of Bahia (UFBA), Av. Adhemar de Barros, s/n, Campus de Ondina, Salvador, Bahia, Brazil"],"raw_orcid":"https://orcid.org/0000-0001-8586-1042","affiliations":[{"raw_affiliation_string":"Formalisms and Semantic Applications Research Group (FORMAS), LaSiD/DCC/IME\u2014Federal University of Bahia (UFBA), Av. Adhemar de Barros, s/n, Campus de Ondina, Salvador, Bahia, Brazil","institution_ids":["https://openalex.org/I126158947"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002539501"],"corresponding_institution_ids":["https://openalex.org/I126158947"],"apc_list":null,"apc_paid":null,"fwci":3.2214,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.93743235,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"25","issue":"2","first_page":"287","last_page":"306"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12016","display_name":"Web Data Mining and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12016","display_name":"Web Data Mining and Analysis","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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":0.9961000084877014,"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":0.9936000108718872,"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":0.8746564388275146},{"id":"https://openalex.org/keywords/transitive-relation","display_name":"Transitive relation","score":0.688117504119873},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6223268508911133},{"id":"https://openalex.org/keywords/portuguese","display_name":"Portuguese","score":0.604219913482666},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5468891859054565},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5384471416473389},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.5124450325965881},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.46787071228027344},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.46638938784599304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4462868571281433},{"id":"https://openalex.org/keywords/data-extraction","display_name":"Data extraction","score":0.44521692395210266},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38213875889778137},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.14534693956375122},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09710687398910522}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8746564388275146},{"id":"https://openalex.org/C191399111","wikidata":"https://www.wikidata.org/wiki/Q64861","display_name":"Transitive relation","level":2,"score":0.688117504119873},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6223268508911133},{"id":"https://openalex.org/C35219183","wikidata":"https://www.wikidata.org/wiki/Q5146","display_name":"Portuguese","level":2,"score":0.604219913482666},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5468891859054565},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5384471416473389},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.5124450325965881},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.46787071228027344},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.46638938784599304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4462868571281433},{"id":"https://openalex.org/C2777466982","wikidata":"https://www.wikidata.org/wiki/Q5227287","display_name":"Data extraction","level":3,"score":0.44521692395210266},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38213875889778137},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.14534693956375122},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09710687398910522},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1017/s135132491800044x","is_oa":false,"landing_page_url":"https://doi.org/10.1017/s135132491800044x","pdf_url":null,"source":{"id":"https://openalex.org/S18088403","display_name":"Natural Language Engineering","issn_l":"1351-3249","issn":["1351-3249","1469-8110"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310311721","host_organization_name":"Cambridge University Press","host_organization_lineage":["https://openalex.org/P4310311721","https://openalex.org/P4310311702"],"host_organization_lineage_names":["Cambridge University Press","University of Cambridge"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Natural Language Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W38873404","https://openalex.org/W95553785","https://openalex.org/W1489930498","https://openalex.org/W1493490255","https://openalex.org/W1529731474","https://openalex.org/W1587341848","https://openalex.org/W1968548280","https://openalex.org/W2126539437","https://openalex.org/W2127978399","https://openalex.org/W2129842875","https://openalex.org/W2134150392","https://openalex.org/W2153804780","https://openalex.org/W2161494021","https://openalex.org/W2162340487","https://openalex.org/W2167187514","https://openalex.org/W2205392349","https://openalex.org/W2249610072","https://openalex.org/W2251687716","https://openalex.org/W2592249290","https://openalex.org/W2617938758","https://openalex.org/W2620968868","https://openalex.org/W2917458986","https://openalex.org/W2930957955","https://openalex.org/W2973055756","https://openalex.org/W4206070857","https://openalex.org/W4285719527","https://openalex.org/W6682780409"],"related_works":["https://openalex.org/W4312527695","https://openalex.org/W2361167282","https://openalex.org/W1528932152","https://openalex.org/W2091342995","https://openalex.org/W1677394555","https://openalex.org/W2271118953","https://openalex.org/W3007067598","https://openalex.org/W1837359179","https://openalex.org/W2165504147","https://openalex.org/W2986643010"],"abstract_inverted_index":{"Abstract":[0],"Nowadays,":[1],"there":[2],"is":[3,22,34,108,141],"an":[4,65],"increasing":[5],"amount":[6],"of":[7,13,20,31,49,54,97,113,130,136],"digital":[8],"data.":[9],"In":[10,60],"the":[11,14,47,84,95,134,144,149],"case":[12],"Web,":[15],"daily,":[16],"a":[17,37,101,111],"vast":[18],"collection":[19],"data":[21,33],"generated,":[23],"whose":[24],"contents":[25],"are":[26],"heterogeneous.":[27],"A":[28],"significant":[29],"portion":[30],"this":[32,61,92],"available":[35],"in":[36,57,75,100,126,148],"natural":[38,58],"language":[39],"format.":[40],"Open":[41,66],"Information":[42],"Extraction":[43],"(Open":[44],"IE)":[45],"enables":[46],"extraction":[48],"facts":[50,71,99],"from":[51,72],"large":[52],"quantities":[53],"texts":[55,73],"written":[56,74],"language.":[59],"work,":[62],"we":[63],"propose":[64],"IE":[67],"method":[68,121],"to":[69,143],"extract":[70],"Portuguese.":[76],"We":[77],"developed":[78],"two":[79],"new":[80],"rules":[81],"that":[82,119],"generalize":[83],"inference":[85,106],"by":[86,89],"transitivity":[87],"and":[88,128],"symmetry.":[90],"Consequently,":[91],"approach":[93,107,140],"increases":[94],"number":[96,129,135],"implicit":[98],"sentence.":[102],"Our":[103,116],"novel":[104],"symmetric":[105,114],"based":[109],"on":[110],"list":[112],"features.":[115],"results":[117],"confirmed":[118],"our":[120,139],"outstands":[122],"close":[123],"works":[124],"both":[125],"precision":[127],"valid":[131],"extractions.":[132],"Considering":[133],"minimal":[137],"facts,":[138],"equivalent":[142],"most":[145],"relevant":[146],"methods":[147],"literature.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":6}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
