By Thomas Hanneforth (auth.), Cerstin Mahlow, Michael Piotrowski (eds.)
From the viewpoint of computational linguistics, morphological assets are the foundation for all higher-level functions. this is often very true for languages with a wealthy morphology, similar to German or Finnish. A morphology part may still therefore be able to interpreting unmarried note varieties in addition to complete corpora. for lots of functional purposes, not just morphological research, but in addition iteration is needed, i.e., the construction of surfaces equivalent to speci?c different types. except makes use of in computational linguistics, there also are various useful - plications that both require morphological research and iteration or which could drastically bene?t from it, for instance, in textual content processing, person interfaces, or info - trieval. those functions have speci?c specifications for morphological elements, together with standards from software program engineering, resembling programming interfaces or robustness. In 1994, the 1st Morpholympics came about on the collage of Erlangen- Nuremberg, a contest among a number of structures for the research and new release of German note kinds. 8 platforms participated within the First Morpholympics; the convention lawsuits [1] hence provide a good assessment of the state-of-the-art in computational morphologyfor German as of 1994.
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Extra resources for State of the Art in Computational Morphology: Workshop on Systems and Frameworks for Computational Morphology, SFCM 2009, Zurich, Switzerland, September 4, 2009. Proceedings
Example text
Lindén, M. Silfverberg, and T. Pirinen The Rule-Variables. Like the X EROX compiler, HFST-T WOL C supports defining a set of similar two-level rules using a rule-schema with variables. During the compilation of the grammar, each schema is compiled into actual two-level rules, by substituting the variables with the values specified for them. All rule-variables, which are used in the grammar, need to be declared in the Rule-variables section. The Sets. It is often convenient to name some classes of symbols, which are used in many rules.
As there is ongoing research in this field [15]. we cannot present a complete word form generation system with conceptualization and linearization. But we show that it is possible to generate a surface form for a given lemma and a given category – a process that is sometimes referred to as surface generation. 1 Surface Generation We distinguish two cases of surface generation: a) the generation of a complete paradigm and b) the generation of a single word form. The first case may be of interest to check the correctness of a grammar, whereas the second case is needed for natural language production in the speaker mode.
Lindén, M. Silfverberg, and T. g. HFST-T WOL C, HFSTL EX C, HFST-C OMPOSE -I NTERSECT, HFST-T EST, HFST-L OOKUP, etc. g. English, Finnish, French, Northern Sámi and Swedish. We used the morphological descriptions for testing the functionality of the tools and for evaluating the performance of the different libraries through a unified interface on the morphological development and compilation tasks. The current article presents some of the main tools that we have created: HFSTL EX C in section 2, HFST-T WOL C in section 3 and HFST-C OMPOSE -I NTERSECT in section 4.