{"id":"https://openalex.org/W2737243082","doi":"https://doi.org/10.18653/v1/d17-1138","title":"Revisiting Selectional Preferences for Coreference Resolution","display_name":"Revisiting Selectional Preferences for Coreference Resolution","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2737243082","doi":"https://doi.org/10.18653/v1/d17-1138","mag":"2737243082"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d17-1138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1138","pdf_url":"https://www.aclweb.org/anthology/D17-1138.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/D17-1138.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073408576","display_name":"Benjamin Heinzerling","orcid":null},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Benjamin Heinzerling","raw_affiliation_strings":["University of Cambridge, Cambridge, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Cambridge, Cambridge, United Kingdom","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054918343","display_name":"Nafise Sadat Moosavi","orcid":"https://orcid.org/0000-0002-8332-307X"},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technische Universit\u00e4t Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Nafise Sadat Moosavi","raw_affiliation_strings":["Technical University of Darmstadt, Darmstadt, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technical University of Darmstadt, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020347604","display_name":"Michael Strube","orcid":"https://orcid.org/0000-0002-4731-8142"},"institutions":[{"id":"https://openalex.org/I71030271","display_name":"Heidelberg Institute for Theoretical Studies","ror":"https://ror.org/01f7bcy98","country_code":"DE","type":"facility","lineage":["https://openalex.org/I71030271"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Michael Strube","raw_affiliation_strings":["Heidelberg Institute for Theoretical Studies, Heidelberg, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Heidelberg Institute for Theoretical Studies, Heidelberg, Germany","institution_ids":["https://openalex.org/I71030271"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1332","last_page":"1339"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9987000226974487,"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":0.9987000226974487,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9972000122070312,"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":0.9952999949455261,"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/coreference","display_name":"Coreference","score":0.9949231147766113},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8343566656112671},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.653529942035675},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.64886474609375},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.515449583530426},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.503710925579071},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4954444169998169},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4769422113895416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08326518535614014},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.05872845649719238}],"concepts":[{"id":"https://openalex.org/C28076734","wikidata":"https://www.wikidata.org/wiki/Q63087","display_name":"Coreference","level":3,"score":0.9949231147766113},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8343566656112671},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.653529942035675},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.64886474609375},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515449583530426},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.503710925579071},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4954444169998169},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4769422113895416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08326518535614014},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.05872845649719238}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.18653/v1/d17-1138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1138","pdf_url":"https://www.aclweb.org/anthology/D17-1138.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:190608","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Proceedings Paper"},{"id":"pmh:oai:arXiv.org:1707.06456","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1707.06456","pdf_url":"https://arxiv.org/pdf/1707.06456","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":"","raw_type":"text"},{"id":"mag:2737243082","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1707.06456.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":"doi:10.48550/arxiv.1707.06456","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1707.06456","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"}],"best_oa_location":{"id":"doi:10.18653/v1/d17-1138","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d17-1138","pdf_url":"https://www.aclweb.org/anthology/D17-1138.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 2017 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3424576390","display_name":null,"funder_award_id":"GRK 1994","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"},{"id":"https://openalex.org/G481299621","display_name":null,"funder_award_id":"GRK 1994/1","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"},{"id":"https://openalex.org/F4320324316","display_name":"Klaus Tschira Stiftung","ror":"https://ror.org/052jep661"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2737243082.pdf","grobid_xml":"https://content.openalex.org/works/W2737243082.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W25333297","https://openalex.org/W1516391399","https://openalex.org/W1521365985","https://openalex.org/W1973942085","https://openalex.org/W2084799720","https://openalex.org/W2094728533","https://openalex.org/W2096423148","https://openalex.org/W2098345921","https://openalex.org/W2168185617","https://openalex.org/W2177614019","https://openalex.org/W2205651080","https://openalex.org/W2250539671","https://openalex.org/W2336260055","https://openalex.org/W2406945108","https://openalex.org/W2409706897","https://openalex.org/W2507397568","https://openalex.org/W2571842322","https://openalex.org/W2593536831","https://openalex.org/W2807410225","https://openalex.org/W2950577311","https://openalex.org/W2962769558","https://openalex.org/W2963167649"],"related_works":["https://openalex.org/W3155267769","https://openalex.org/W2894706950","https://openalex.org/W2124214517","https://openalex.org/W2109733898","https://openalex.org/W2103095311","https://openalex.org/W2281678207","https://openalex.org/W47123560","https://openalex.org/W2180160918","https://openalex.org/W3103318178","https://openalex.org/W2251517114","https://openalex.org/W3208142922","https://openalex.org/W3214156274","https://openalex.org/W3196673752","https://openalex.org/W2026421491","https://openalex.org/W2410503294","https://openalex.org/W2139354869","https://openalex.org/W3198661095","https://openalex.org/W2162471830","https://openalex.org/W1495981708","https://openalex.org/W3098526042"],"abstract_inverted_index":{"Selectional":[0],"preferences":[1,31],"have":[2],"long":[3],"been":[4],"claimed":[5],"to":[6,85],"be":[7],"essential":[8],"for":[9],"coreference":[10,21,49],"resolution.":[11],"However,":[12,65],"they":[13],"are":[14],"mainly":[15],"modeled":[16],"only":[17],"implicitly":[18,88],"by":[19],"current":[20],"resolvers.":[22],"We":[23,40],"propose":[24],"a":[25,61,69,93],"dependencybased":[26],"embedding":[27],"model":[28,47],"of":[29,45,60],"selectional":[30],"which":[32],"allows":[33],"fine-grained":[34],"compatibility":[35],"judgments":[36],"with":[37,68],"high":[38],"coverage.":[39],"show":[41],"that":[42,71],"the":[43,53,57],"incorporation":[44],"our":[46],"improves":[48],"resolution":[50],"performance":[51],"on":[52],"CoNLL":[54],"dataset,":[55],"matching":[56],"state-of-the-art":[58],"results":[59],"more":[62],"complex":[63],"system.":[64],"it":[66,73],"comes":[67],"cost":[70],"makes":[72],"debatable":[74],"how":[75],"worthwhile":[76],"such":[77],"improvements":[78],"are.":[79],"*":[80],"These":[81],"authors":[82],"contributed":[83],"equally":[84],"this":[86],"work.":[87],"at":[89],"best,":[90],"e.g.,":[91],"via":[92],"given":[94],"mention's":[95],"dependency":[96],"governor":[97],"and":[98],"other":[99],"contextual":[100],"features.":[101]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}