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Treebank-Based Grammar Acquisition for German

  • Manual development of deep linguistic resources is time-consuming and costly and therefore often described as a bottleneck for traditional rule-based NLP. In my PhD thesis I present a treebank-based method for the automatic acquisition of LFG resources for German. The method automatically creates deep and rich linguistic presentations from labelled data (treebanks) and can be applied to large data sets. My research is based on and substantially extends previous work on automatically acquiring wide-coverage, deep, constraint-based grammatical resources from the English Penn-II treebank (Cahill et al.,2002; Burke et al., 2004; Cahill, 2004). Best results for English show a dependency f-score of 82.73% (Cahill et al., 2008) against the PARC 700 dependency bank, outperforming the best hand-crafted grammar of Kaplan et al. (2004). Preliminary work has been carried out to test the approach on languages other than English, providing proof of concept for the applicability of the method (Cahill et al., 2003; Cahill, 2004; Cahill et al., 2005). While first results have been promising, a number of important research questions have been raised. The original approach presented first in Cahill et al. (2002) is strongly tailored to English and the datastructures provided by the Penn-II treebank (Marcus et al., 1993). English is configurational and rather poor in inflectional forms. German, by contrast, features semi-free word order and a much richer morphology. Furthermore, treebanks for German differ considerably from the Penn-II treebank as regards data structures and encoding schemes underlying the grammar acquisition task. In my thesis I examine the impact of language-specific properties of German as well as linguistically motivated treebank design decisions on PCFG parsing and LFG grammar acquisition. I present experiments investigating the influence of treebank design on PCFG parsing and show which type of representations are useful for the PCFG and LFG grammar acquisition tasks. Furthermore, I present a novel approach to cross-treebank comparison, measuring the effect of controlled error insertion on treebank trees and parser output from different treebanks. I complement the cross-treebank comparison by providing a human evaluation using TePaCoC, a new testsuite for testing parser performance on complex grammatical constructions. Manual evaluation on TePaCoC data provides new insights on the impact of flat vs. hierarchical annotation schemes on data-driven parsing. I present treebank-based LFG acquisition methodologies for two German treebanks. An extensive evaluation along different dimensions complements the investigation and provides valuable insights for the future development of treebanks.

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Metadaten
Author:Ines Rehbein
URN:urn:nbn:de:hebis:30:3-330238
Publisher:Dublin City University
Place of publication:Dublin
Advisor:Josef van Genabith
Document Type:Doctoral Thesis
Language:English
Year of first Publication:2009
Date of Publication (online):2017/01/09
Publicationstate:Veröffentlichungsversion
Reviewstate:Qualifikationsarbeit (Dissertation, Habilitationsschrift)
Tag:German; LFG; PCFG; grammar acquisistion; lexical-functional grammar; parsing; treebanks
GND Keyword:Korpus <Linguistik>; Syntaktische Analyse
Pagenumber:249
Note:
This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License: http://doras.dcu.ie/licenses/ccancnd3_0/
Dewey Decimal Classification:400 Sprache / 430 Deutsch
BDSL-Classification:Grammatik
Linguistics-Classification:Computerlinguistik
Linguistics-Classification:Grammatikforschung
Linguistics-Classification:Korpuslinguistik
Open Access?:Ja
Licence (German):License LogoCreative Commons - Namensnennung-Keine kommerzielle Nutzung-Weitergabe unter gleichen Bedingungen 3.0 Deutschland