{"id":"https://openalex.org/W2169410519","doi":"https://doi.org/10.3115/1118693.1118707","title":"Fast LR parsing using rich (Tree Adjoining) Grammars","display_name":"Fast LR parsing using rich (Tree Adjoining) Grammars","publication_year":2002,"publication_date":"2002-01-01","ids":{"openalex":"https://openalex.org/W2169410519","doi":"https://doi.org/10.3115/1118693.1118707","mag":"2169410519"},"language":"en","primary_location":{"id":"doi:10.3115/1118693.1118707","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118707","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118707","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118707","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012134890","display_name":"Carlos A. Prolo","orcid":null},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Carlos A. Prolo","raw_affiliation_strings":["University of Pennsylvania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Pennsylvania","institution_ids":["https://openalex.org/I36788626"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012134890"],"corresponding_institution_ids":["https://openalex.org/I36788626"],"apc_list":null,"apc_paid":null,"fwci":0.5615,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.67921825,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":96},"biblio":{"volume":"10","issue":null,"first_page":"103","last_page":"110"},"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":0.9987999796867371,"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":0.9857000112533569,"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":0.7873569130897522},{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.6870438456535339},{"id":"https://openalex.org/keywords/rule-based-machine-translation","display_name":"Rule-based machine translation","score":0.5698508024215698},{"id":"https://openalex.org/keywords/treebank","display_name":"Treebank","score":0.5531109571456909},{"id":"https://openalex.org/keywords/lr-parser","display_name":"LR parser","score":0.5514600276947021},{"id":"https://openalex.org/keywords/tree-adjoining-grammar","display_name":"Tree-adjoining grammar","score":0.5409799814224243},{"id":"https://openalex.org/keywords/top-down-parsing","display_name":"Top-down parsing","score":0.5367136597633362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5049379467964172},{"id":"https://openalex.org/keywords/parsing-expression-grammar","display_name":"Parsing expression grammar","score":0.4980292320251465},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4910573959350586},{"id":"https://openalex.org/keywords/s-attributed-grammar","display_name":"S-attributed grammar","score":0.4562680423259735},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.44534391164779663},{"id":"https://openalex.org/keywords/l-attributed-grammar","display_name":"L-attributed grammar","score":0.39462101459503174},{"id":"https://openalex.org/keywords/context-free-grammar","display_name":"Context-free grammar","score":0.2683652639389038}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7873569130897522},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.6870438456535339},{"id":"https://openalex.org/C53893814","wikidata":"https://www.wikidata.org/wiki/Q7378909","display_name":"Rule-based machine translation","level":2,"score":0.5698508024215698},{"id":"https://openalex.org/C206134035","wikidata":"https://www.wikidata.org/wiki/Q811525","display_name":"Treebank","level":3,"score":0.5531109571456909},{"id":"https://openalex.org/C35164859","wikidata":"https://www.wikidata.org/wiki/Q1756442","display_name":"LR parser","level":4,"score":0.5514600276947021},{"id":"https://openalex.org/C134083981","wikidata":"https://www.wikidata.org/wiki/Q1754022","display_name":"Tree-adjoining grammar","level":4,"score":0.5409799814224243},{"id":"https://openalex.org/C42560504","wikidata":"https://www.wikidata.org/wiki/Q15419395","display_name":"Top-down parsing","level":3,"score":0.5367136597633362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5049379467964172},{"id":"https://openalex.org/C146810361","wikidata":"https://www.wikidata.org/wiki/Q32271","display_name":"Parsing expression grammar","level":5,"score":0.4980292320251465},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4910573959350586},{"id":"https://openalex.org/C147547768","wikidata":"https://www.wikidata.org/wiki/Q3113342","display_name":"S-attributed grammar","level":3,"score":0.4562680423259735},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.44534391164779663},{"id":"https://openalex.org/C67621940","wikidata":"https://www.wikidata.org/wiki/Q3113340","display_name":"L-attributed grammar","level":4,"score":0.39462101459503174},{"id":"https://openalex.org/C97212296","wikidata":"https://www.wikidata.org/wiki/Q338047","display_name":"Context-free grammar","level":3,"score":0.2683652639389038}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3115/1118693.1118707","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118707","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118707","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.5.8309","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.8309","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://acl.ldc.upenn.edu/W/W02/W02-1014.pdf","raw_type":"text"}],"best_oa_location":{"id":"doi:10.3115/1118693.1118707","is_oa":true,"landing_page_url":"https://doi.org/10.3115/1118693.1118707","pdf_url":"https://dl.acm.org/doi/pdf/10.3115/1118693.1118707","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACL-02 conference on Empirical methods in natural language processing - EMNLP '02","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2169410519.pdf","grobid_xml":"https://content.openalex.org/works/W2169410519.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W93150917","https://openalex.org/W1479758177","https://openalex.org/W1527008920","https://openalex.org/W1533941743","https://openalex.org/W1542327949","https://openalex.org/W1564942370","https://openalex.org/W1577934069","https://openalex.org/W1594453148","https://openalex.org/W1605351056","https://openalex.org/W1677141046","https://openalex.org/W1819340723","https://openalex.org/W1976629384","https://openalex.org/W1986543644","https://openalex.org/W1988472526","https://openalex.org/W2059000558","https://openalex.org/W2064490449","https://openalex.org/W2081451375","https://openalex.org/W2087165009","https://openalex.org/W2093647425","https://openalex.org/W2107771181","https://openalex.org/W2110651511","https://openalex.org/W2130630493","https://openalex.org/W2130747650","https://openalex.org/W2130753752","https://openalex.org/W2142099059","https://openalex.org/W2142463934","https://openalex.org/W2146635133","https://openalex.org/W2158567261","https://openalex.org/W2788296320","https://openalex.org/W3037413987","https://openalex.org/W3037802291","https://openalex.org/W3088930208","https://openalex.org/W4213279391","https://openalex.org/W4234977471","https://openalex.org/W4236259128","https://openalex.org/W4244423947"],"related_works":["https://openalex.org/W2090257971","https://openalex.org/W1560736395","https://openalex.org/W4320024782","https://openalex.org/W2116566824","https://openalex.org/W2772054157","https://openalex.org/W2246820938","https://openalex.org/W2175212756","https://openalex.org/W2943197582","https://openalex.org/W2077094028","https://openalex.org/W2164260211"],"abstract_inverted_index":{"We":[0,28],"describe":[1],"an":[2],"LR":[3,53],"parser":[4,31],"of":[5,26,59],"parts-of-speech":[6],"(and":[7],"punctuation":[8],"labels)":[9],"for":[10],"Tree":[11],"Adjoining":[12],"Grammars":[13],"(TAGs),":[14],"that":[15,37,52],"solves":[16],"table":[17],"conflicts":[18],"in":[19],"a":[20],"greedy":[21],"way,":[22],"with":[23,44],"limited":[24],"amount":[25],"backtracking.":[27],"evaluate":[29],"the":[30,33,38,50,57],"using":[32],"Penn":[34],"Treebank":[35],"showing":[36],"method":[39],"yield":[40],"very":[41],"fast":[42],"parsers":[43],"at":[45],"least":[46],"reasonable":[47],"accuracy,":[48],"confirming":[49],"intuition":[51],"parsing":[54],"benefits":[55],"from":[56],"use":[58],"rich":[60],"grammars.":[61]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2016,"cited_by_count":2}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2025-10-10T00:00:00"}
