. . "Avignon, France" . "http://www.aclweb.org/anthology/W/W12/W12-0503" . . . . . "\u017Dabokrtsk\u00FD, Zden\u011Bk" . "Green, Nathan David" . "Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser" . "Dependency parsing has made many advancements in recent years, in particular for English. There are a few dependency parsers that achieve comparable accuracy scores with each other but with very different types of errors. This paper examines creating a new dependency structure through ensemble learning using a hybrid of the outputs of various parsers. We combine all tree outputs into a weighted edge graph, using 4 weighting mechanisms. The weighted edge graph is the input into our ensemble system and is a hybrid of very different parsing techniques (constituent parsers, transition-based dependency parsers, and a graph-based parser). From this graph we take a maximum spanning tree. We examine the new dependency structure in terms of accuracy and errors on individual part-of-speech values. The results indicate that using a greater number of more varied parsers will improve accuracy results. The combined ensemble system, using 5 parsers based on 3 different parsing techniques, achieves an accuracy score"@en . "2"^^ . "2012-04-23+02:00"^^ . "RIV/00216208:11320/12:10130050!RIV13-MSM-11320___" . . "[02FE4FE587AB]" . . "978-1-937284-19-0" . "Association for Computational Linguistics" . . . "11320" . . . "R" . "8"^^ . . "Green, Nathan David" . "Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser" . "Dependency parsing has made many advancements in recent years, in particular for English. There are a few dependency parsers that achieve comparable accuracy scores with each other but with very different types of errors. This paper examines creating a new dependency structure through ensemble learning using a hybrid of the outputs of various parsers. We combine all tree outputs into a weighted edge graph, using 4 weighting mechanisms. The weighted edge graph is the input into our ensemble system and is a hybrid of very different parsing techniques (constituent parsers, transition-based dependency parsers, and a graph-based parser). From this graph we take a maximum spanning tree. We examine the new dependency structure in terms of accuracy and errors on individual part-of-speech values. The results indicate that using a greater number of more varied parsers will improve accuracy results. The combined ensemble system, using 5 parsers based on 3 different parsing techniques, achieves an accuracy score" . . . "Proceedings of the Workshop on Innovative Hybrid Approaches to the Processing of Textual Data" . "139939" . . . "Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser"@en . . . "parser; dependency; ensemble; into; trees; dependency; constituency; combination; hybrid"@en . . "2"^^ . "RIV/00216208:11320/12:10130050" . . "Hybrid Combination of Constituency and Dependency Trees into an Ensemble Dependency Parser"@en . "Avignon, France" .