Abstract. Multiword expressions are a key problem for the development of large-scale, linguistically sound natural language processing technology. This paper surveys the problem and some currently available analytic techniques. The various kinds of multiword expressions should be analyzed in distinct ways, including listing "words with spaces", hierarchically organized lexicons, restricted combinatoric rules, lexical selection, "idiomatic constructions" and simple statistical affinity. An adequate comprehensive analysis of multiword expressions must employ both symbolic and statistical techniques.
This paper examines Determinerless PPs in English from a theoretical perspective. We classify attested P + N combinations across a number of analytic dimensions, arguing that the observed cases fall into at least three distinct classes. We then survey three different analytic methods that can predict the behaviour of the differing classes and examine various remaining difficult cases that may remain as challenges.
Article choice can pose difficult problems in applications such as machine translation and automated summarization. In this paper, we investigate the use of corpus data to collect statistical generalizations about article use in English in order to be able to generate articles automatically to supplement a symbolic generator. We use data from the Penn Treebank as input to a memory-based learner (TiMBL 3.0;Daelemans et al., 2000) which predicts whether to generate an article with respect to an English base noun phrase. We discuss competitive results obtained using a variety of lexical, syntactic and semantic features that play an important role in automated article generation.
After a long history of compilation of our own lexical resources, EDR Japanese/English Electronic Dictionary, and discussions with major players on development of various WordNets, Japanese National Institute of Information and Communications Technology started developing the Japanese WordNet in 2006 and will publicly release the first version, which includes both the synset in Japanese and the annotated Japanese corpus of SemCor, in June 2008. As the first step in compiling the Japanese WordNet, we added Japanese equivalents to synsets of the Princeton WordNet. Of course, we must also add some synsets which do not exist in the Princeton WordNet, and must modify synsets in the Princeton WordNet, in order to make the hierarchical structure of Princeton synsets represent thesaurus-like information found in the Japanese language, however, we will address these tasks in a future study. We then translated English sentences which are used in the SemCor annotation into Japanese and annotated them using our Japanese WordNet. This article describes the overview of our project to compile Japanese WordNet and other resources which relate to our Japanese WordNet.
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