String similarity metrics are used for several purposes in text-processing. One task is the extraction of cognates from bilingual text. In this paper three approaches to the automatic generation of language dependent string matching functions are present

The focus of this thesis is on re-using translations in natural language processing. It involves the collection of documents and their translations in an appropriate format, the automatic extraction of translation data, and the application of the extracted data to different tasks in natural language processing.

Five parallel corpora containing more than 35 million words in 60 languages have been collected within co-operative projects. All corpora are sentence aligned and parts of them have been analyzed automatically and annotated with linguistic markup.

Lexical data are extracted from the corpora by means of word alignment. Two automatic word alignment systems have been developed, the Uppsala Word Aligner (UWA) and the Clue Aligner. UWA implements an iterative "knowledge-poor" word alignment approach using association measures and alignment heuristics. The Clue Aligner provides an innovative framework for the combination of statistical and linguistic resources in aligning single words and multi-word units. Both aligners have been applied to several corpora. Detailed evaluations of the alignment results have been carried out for three of them using fine-grained evaluation techniques.

A corpus processing toolbox, Uplug, has been developed. It includes the implementation of UWA and is freely available for research purposes. A new version, Uplug II, includes the Clue Aligner. It can be used via an experimental web interface (UplugWeb).

Lexical data extracted by the word aligners have been applied to different tasks in computational lexicography and machine translation. The use of word alignment in monolingual lexicography has been investigated in two studies. In a third study, the feasibility of using the extracted data in interactive machine translation has been demonstrated. Finally, extracted lexical data have been used for enhancing the lexical components of two machine translation systems.

Verbs have a central role in language processing but simultaneously verbs tend to represent a greater cognitive load on processing than nouns. An important characteristic of the verb lexicon is that in all languages, a small number of verbs appear to be d

The polysemy of the Swedish verb ge ’give’is described and contrasted to English give based on data from the English Swedish Parallel Corpus (ESPC). The major extended uses of Swedish ge have parallels in other languages judging from the typological descr

The Swedish WordNet project aims at building a Swedish version of the EuroWordNet lexical database. The article accounts for some of the problems specific to the building of a Swedish net. As an illustration, three examples are discussed: the coding of w

This is a status report of the rule-based machine translation system MATS (Sågvall Hein et al., 2002). It describes the development into its current state, which has recently been focused on extending the linguistic resources to new domains and improving robustness. Incases where an input sentence is not fully processable by the system, partial results are taken care of and used in producing a translationby complementary methods. A road-map for future development is also sketched.