Dependency parsing with finite state transducers and compression rules

TítuloDependency parsing with finite state transducers and compression rules
AutoresPablo Gamallo and Marcos Garcia
TipoArtículo de revista
Fonte Information Processing and Management, PERGAMON-ELSEVIER SCIENCE LTD, Vol. 6, No. 54, pp. 1244-1261 , 2018.
RankProvisionally ranked Q1 in Library and Information Sciences by SJR 2017
ISSN0306-4573
DOI10.1016/j.ipm.2018.05.003
AbstractThis article proposes a syntactic parsing strategy based on a dependency grammar containing formal rules and a compression technique that reduces the complexity of those rules. Compression parsing is mainly driven by the ‘single-head’ constraint of Dependency Grammar, and can be seen as an alternative method to the well-known constructive strategy. The compression algorithm simplifies the input sentence by progressively removing from it the dependent tokens as soon as binary syntactic dependencies are recognized. This strategy is thus similar to that used in deterministic dependency parsing. A compression parser was implemented and released under General Public License, as well as a cross-lingual grammar with Universal Dependencies, containing only broad-coverage rules applied to Romance languages. The system is an almost delexicalized parser which does not need training data to analyze Romance languages. The rule-based cross-lingual parser was submitted to CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies. The performance of our system was compared to the other supervised systems participating in the competition, paying special attention to the parsing of different treebanks of the same language. We also trained a supervised delexicalized parser for Romance languages in order to compare it to our rule-based system. The results show that the performance of our cross-lingual method does not change across related languages and across different treebanks, while most supervised methods turn out to be very dependent on the text domain used to train the system.
Palabras chaveSyntactic Parsing, Dependency Grammar, Universal Dependencies, Finite State Transducers