Paul Meurer

Speeding up LFG Parsing Using C-Structure Pruning

In this paper we present a method for greatly reducing parse times in LFG parsing, while at the same time maintaining parse accuracy. We evaluate the methodology on data from English, German and Norwegian and show that the same patterns hold across languages. We achieve a speedup of 67% on the English data and 49% on the German data. On a small amount of data for Norwegian, we achieve a speedup of 40%, although with more training data we expect this figure to increase.

A Computational Grammar for Georgian

In this paper, I give an overview of an ongoing project which aims at building a full-scale computational grammar for Georgian in the Lexical Functional Grammar framework and try to illustrate both practical and theoretical aspects of grammar development. The rich and complex morphology of the language is a major challenge when building a computational grammar for Georgian that is meant to be more than a toy system. I discuss my treatment of the morphology and show how morphology interfaces with syntax. I then illustrate how some of the main syntactic constructions of the language are implemented in the grammar. Finally, I present the indispensable tools that are used in developing the grammar system: fst ; the xle parsing platform, the LFG Parsebanker, and a large searchable corpus of non-fiction and fiction texts.

The enrichment of lexical resources through incremental parsebanking

Automatic syntactic analysis of a corpus requires detailed lexical and morphological information that cannot always be harvested from traditional dictionaries. Therefore the development of a treebank presents an opportunity to simultaneously enrich the lexicon. In building NorGramBank, we use an incremental parsebanking approach, in which a corpus is parsed and disambiguated, and after improvements to the grammar and the lexicon, reparsed. In this context we have implemented a text preprocessing interface where annotators can enter unknown words or missing lexical information either before parsing or during disambiguation. The information added to the lexicon in this way may be of great interest both to lexicographers and to other language technology efforts.

A finite state approach to Abkhaz morphology and stress

The West Caucasian language Abkhaz is characterized by a rich but rather regular agglutinative morphology. Word stress, however, is free and dynamic and difficult to predict. A theory of stress in Abkhaz has been developed by V. Dybo, A. Spruit and L. Trigo which predicts word stress correctly in the majority of cases. Although stress is not orthographically marked, its position determines the surface representation of Schwa. Thus, in a morphological analyser for the language, stress rules have to be incorporated in order to be able to properly parse and generate orthographic forms. I show how a finite state morphological analyser for Abkhaz can be built that uses the rules developed by Trigo et al.