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: | ; ; ; |
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| 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 |
| Summary: | ‘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 |
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