{"id":"https://openalex.org/W2622587213","doi":"https://doi.org/10.18653/v1/w17-0813","title":"Catching the Common Cause: Extraction and Annotation of Causal Relations and their Participants","display_name":"Catching the Common Cause: Extraction and Annotation of Causal Relations and their Participants","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2622587213","doi":"https://doi.org/10.18653/v1/w17-0813","mag":"2622587213"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w17-0813","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0813","pdf_url":"https://www.aclweb.org/anthology/W17-0813.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 11th Linguistic Annotation Workshop","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W17-0813.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064974921","display_name":"Ines Rehbein","orcid":"https://orcid.org/0000-0002-9615-6389"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ines Rehbein","raw_affiliation_strings":["Leibniz Science Campus \"Empirical Linguistics and Computational Language Modeling\"","IDS Mannheim/University of Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz Science Campus \"Empirical Linguistics and Computational Language Modeling\"","institution_ids":[]},{"raw_affiliation_string":"IDS Mannheim/University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011827545","display_name":"Josef Ruppenhofer","orcid":"https://orcid.org/0000-0002-8662-7618"},"institutions":[{"id":"https://openalex.org/I223822909","display_name":"Heidelberg University","ror":"https://ror.org/038t36y30","country_code":"DE","type":"education","lineage":["https://openalex.org/I223822909"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Josef Ruppenhofer","raw_affiliation_strings":["Leibniz Science Campus \"Empirical Linguistics and Computational Language Modeling\"","IDS Mannheim/University of Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Leibniz Science Campus \"Empirical Linguistics and Computational Language Modeling\"","institution_ids":[]},{"raw_affiliation_string":"IDS Mannheim/University of Heidelberg, Germany","institution_ids":["https://openalex.org/I223822909"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I223822909"],"apc_list":null,"apc_paid":null,"fwci":0.826,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.80193695,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"105","last_page":"114"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","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/T10181","display_name":"Natural Language Processing Techniques","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/T10028","display_name":"Topic Modeling","score":0.9994999766349792,"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":0.9829999804496765,"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/lexicon","display_name":"Lexicon","score":0.8265718221664429},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7926925420761108},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.7409891486167908},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.6773889660835266},{"id":"https://openalex.org/keywords/causality","display_name":"Causality (physics)","score":0.6566818952560425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6052083373069763},{"id":"https://openalex.org/keywords/german","display_name":"German","score":0.5890054702758789},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5816145539283752},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5094824433326721},{"id":"https://openalex.org/keywords/verb","display_name":"Verb","score":0.5057435035705566},{"id":"https://openalex.org/keywords/relationship-extraction","display_name":"Relationship extraction","score":0.4415138065814972},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.3717386722564697},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.3185397982597351}],"concepts":[{"id":"https://openalex.org/C2778121359","wikidata":"https://www.wikidata.org/wiki/Q8096","display_name":"Lexicon","level":2,"score":0.8265718221664429},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7926925420761108},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.7409891486167908},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.6773889660835266},{"id":"https://openalex.org/C64357122","wikidata":"https://www.wikidata.org/wiki/Q1149766","display_name":"Causality (physics)","level":2,"score":0.6566818952560425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6052083373069763},{"id":"https://openalex.org/C154775046","wikidata":"https://www.wikidata.org/wiki/Q188","display_name":"German","level":2,"score":0.5890054702758789},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5816145539283752},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5094824433326721},{"id":"https://openalex.org/C2776397901","wikidata":"https://www.wikidata.org/wiki/Q24905","display_name":"Verb","level":2,"score":0.5057435035705566},{"id":"https://openalex.org/C153604712","wikidata":"https://www.wikidata.org/wiki/Q7310755","display_name":"Relationship extraction","level":3,"score":0.4415138065814972},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.3717386722564697},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.3185397982597351},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/w17-0813","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0813","pdf_url":"https://www.aclweb.org/anthology/W17-0813.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 11th Linguistic Annotation Workshop","raw_type":"proceedings-article"},{"id":"pmh:oai:ids-pub.bsz-bw.de:6153","is_oa":false,"landing_page_url":"https://nbn-resolving.org/urn:nbn:de:bsz:mh39-61534","pdf_url":null,"source":{"id":"https://openalex.org/S4306401750","display_name":"Publication Server of the Institute for German Language (Institute for German Language)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210099471","host_organization_name":"Leibniz Institute for the German Language","host_organization_lineage":["https://openalex.org/I4210099471"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"conferenceobject"}],"best_oa_location":{"id":"doi:10.18653/v1/w17-0813","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-0813","pdf_url":"https://www.aclweb.org/anthology/W17-0813.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 11th Linguistic Annotation Workshop","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G6604464234","display_name":null,"funder_award_id":"SAS-2015","funder_id":"https://openalex.org/F4320334763","funder_display_name":"Leibniz-Gemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320334763","display_name":"Leibniz-Gemeinschaft","ror":"https://ror.org/01n6r0e97"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2622587213.pdf","grobid_xml":"https://content.openalex.org/works/W2622587213.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W22168010","https://openalex.org/W86588477","https://openalex.org/W305900312","https://openalex.org/W1517744545","https://openalex.org/W1763753566","https://openalex.org/W1936029161","https://openalex.org/W1964575979","https://openalex.org/W1979701466","https://openalex.org/W2047317708","https://openalex.org/W2065675538","https://openalex.org/W2081580037","https://openalex.org/W2084829134","https://openalex.org/W2119325477","https://openalex.org/W2133229022","https://openalex.org/W2142321231","https://openalex.org/W2166957049","https://openalex.org/W2183656857","https://openalex.org/W2248607539","https://openalex.org/W2250861254","https://openalex.org/W2251358367","https://openalex.org/W2251766678","https://openalex.org/W2251837567","https://openalex.org/W2508239101","https://openalex.org/W2575451680","https://openalex.org/W2577260496","https://openalex.org/W2948533454","https://openalex.org/W4244575301","https://openalex.org/W4250143236","https://openalex.org/W4386506836"],"related_works":["https://openalex.org/W2352298027","https://openalex.org/W4319940250","https://openalex.org/W842810586","https://openalex.org/W2092919065","https://openalex.org/W4236762297","https://openalex.org/W3138801416","https://openalex.org/W2369351710","https://openalex.org/W2594363579","https://openalex.org/W2169232658","https://openalex.org/W2444550338"],"abstract_inverted_index":{"In":[0],"this":[1,31],"paper,":[2],"we":[3],"present":[4],"a":[5,23,36,48,70,87,101],"simple,":[6],"yet":[7],"effective":[8],"method":[9,99],"for":[10,39,75,89],"the":[11,59,62,115,127,135],"automatic":[12,90],"identification":[13],"and":[14,65,126],"extraction":[15],"of":[16,30,47,61,92,103,108],"causal":[17,41,63,93],"relations":[18],"from":[19],"text,":[20],"based":[21],"on":[22,96],"large":[24],"English-German":[25],"parallel":[26],"corpus.":[27],"The":[28,43,124],"goal":[29],"effort":[32],"is":[33],"to":[34,85,134],"create":[35],"lexical":[37,106],"resource":[38,44],"German":[40],"relations.":[42,94],"will":[45,66,130],"consist":[46],"lexicon":[49,125],"that":[50,53,78],"describes":[51],"constructions":[52],"trigger":[54],"causality":[55],"as":[56,58,82],"well":[57],"participants":[60],"event,":[64],"be":[67,80,131],"augmented":[68],"by":[69],"corpus":[71,118],"with":[72],"annotated":[73,122,128],"instances":[74],"each":[76],"entry,":[77],"can":[79],"used":[81],"training":[83],"data":[84,129],"develop":[86],"system":[88],"classification":[91],"Focusing":[95],"verbs,":[97],"our":[98,117],"harvested":[100],"set":[102],"100":[104],"different":[105],"triggers":[107],"causality,":[109],"including":[110],"support":[111],"verb":[112],"constructions.":[113],"At":[114],"moment,":[116],"includes":[119],"over":[120],"1,000":[121],"instances.":[123],"made":[132],"available":[133],"research":[136],"community.":[137]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
