Programme booklet (pdf)

94
CLIN 21 – CONFERENCE PROGRAMME
Towards a language-independent data-driven compound
decomposition tool
Abstract
Réveil, Bert 1 and Macken, Lieve 2
1 ELIS, Ghent University
2 LT3, Language and Translation Technology Team
Compounding is a highly productive process in Dutch that poses a challenge for various
NLP applications such as terminology extraction, continuous speech recognition, and
automated word alignment. The present work therefore proposes a languageindependent,
data-driven decomposition tool that tries to segment compounds into
their meaningful parts.
The basic version of this tool initially determines a list of eligible compound
constituents (so-called heads and tails), relying solely on word frequency information
that is extracted from a large text corpus. The decomposition algorithm then
recursively attempts to decompose the compounds, allowing only two-part head-tail
divisions in each iteration. E.g. the noun 'postzegelverzamelaar' is first split into
'postzegel' + 'verzamelaar', followed by an additional decomposition of 'postzegel' into
'post' + 'zegel'.
Apart from the basic version, an extended version of the tool is assessed that uses PoS
information as a means to restrict the list of possible heads and tails. The preformance
of both versions is evaluated in two large-scale decomposition experiments, one on the
E-lex compound list and one on a word list that contains specific vocabulary from the
automotive domain. As the presented decomposition tool only relates on word
frequency and PoS information, it is expected that the tool can be easily adapted to
new domains and languages.
Corresponding author: breveil@elis.ugent.be