Data-driven deep-syntactic dependency parsing
‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency p...
| Authors: | ; ; ; |
|---|---|
| Format: | Article |
| Status: | Accepted version |
| Publication date: | 2016 |
| Country: | España |
| Institution: | Universitat Pompeu Fabra |
| Repository: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/27951 |
| Online Access: | http://hdl.handle.net/10230/27951 http://dx.doi.org/10.1017/S1351324915000285 |
| Access Level: | Embargoed access |
| Keyword: | Processament del llenguatge natural Tractament del llenguatge natural (Informàtica) Lingüística computacional |
| _version_ | 1878740007041105920 |
|---|---|
| author | Ballesteros, Miguel |
| author2 | Bohnet, Bernd Mille, Simon Wanner, Leo |
| author2_role | author author author |
| author_browse | Ballesteros, Miguel Bohnet, Bernd Mille, Simon Wanner, Leo |
| author_facet | Ballesteros, Miguel Bohnet, Bernd Mille, Simon Wanner, Leo |
| author_role | author |
| collection | Repositorio Digital de la UPF |
| description | ‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency parser (connected trees defined over all words of a sentence and/nlanguage-specific grammatical functions) and the output of a semantic parser (forests of trees/ndefined over individual lexemes or phrasal chunks and abstract semantic role labels which/ncapture the frame structures of predicative elements and drop all attributive and coordinative/ndependencies). We propose a parser that provides deep-syntactic structures. The parser has/nbeen tested on Spanish, English and Chinese |
| eu_rights_str_mv | embargoedAccess |
| format | article |
| id | ES_cbfb9b5de8e752458f00a39087dcee60 |
| institution | Universitat Pompeu Fabra |
| instname_str | Universitat Pompeu Fabra |
| network_acronym_str | ES |
| network_name_str | España |
| oai_identifier_str | oai:repositori.upf.edu:10230/27951 |
| publishDate | 2016 |
| publishDateSort | 2016 |
| publisher | Cambridge University Press |
| publisherStr | Cambridge University Press |
| reponame_str | Repositorio Digital de la UPF |
| spelling | Data-driven deep-syntactic dependency parsing Ballesteros, Miguel Bohnet, Bernd Mille, Simon Wanner, Leo Processament del llenguatge natural Tractament del llenguatge natural (Informàtica) Lingüística computacional ‘Deep-syntactic’ dependency structures that capture the argumentative, attributive and co-/nordinative relations between full words of a sentence have a great potential for a number/nof NLP-applications. The abstraction degree of these structures is in between the output/nof a syntactic dependency parser (connected trees defined over all words of a sentence and/nlanguage-specific grammatical functions) and the output of a semantic parser (forests of trees/ndefined over individual lexemes or phrasal chunks and abstract semantic role labels which/ncapture the frame structures of predicative elements and drop all attributive and coordinative/ndependencies). We propose a parser that provides deep-syntactic structures. The parser has/nbeen tested on Spanish, English and Chinese The work reported on in this paper has been partially funded by the European Commission under the contract numbers FP7-ICT-610411 (MULTISENSOR) and H2020-645012-RIA (KRISTINA). Cambridge University Press http://hdl.handle.net/10230/27951 http://dx.doi.org/10.1017/S1351324915000285 |
| spellingShingle | Data-driven deep-syntactic dependency parsing Ballesteros, Miguel Processament del llenguatge natural Tractament del llenguatge natural (Informàtica) Lingüística computacional |
| status_str | acceptedVersion |
| title | Data-driven deep-syntactic dependency parsing |
| title_full | Data-driven deep-syntactic dependency parsing |
| title_fullStr | Data-driven deep-syntactic dependency parsing |
| title_full_unstemmed | Data-driven deep-syntactic dependency parsing |
| title_short | Data-driven deep-syntactic dependency parsing |
| title_sort | Data-driven deep-syntactic dependency parsing |
| topic | Processament del llenguatge natural Tractament del llenguatge natural (Informàtica) Lingüística computacional |
| topic_facet | Processament del llenguatge natural Tractament del llenguatge natural (Informàtica) Lingüística computacional |
| url | http://hdl.handle.net/10230/27951 http://dx.doi.org/10.1017/S1351324915000285 |