Evaluation for morphologically rich language: Russian NLP
Abstract - RU-EVAL is a biennial event organized in order to estimate the state of the art in Russian NLP resources, methods and toolkits and to compare various methods and principles implemented for Russian. Russian could be treated as an under-resourced language due to the lack of free distributable gold standard corpora for different NLP tasks (each team tried to work out their own standards). Thus, our goal was to work out the uniform basis for comparison of systems based on different theoretical and engineering approaches, to build evaluation resources, to provide a flexible system of evaluation in order to differentiate between non-acceptable and linguistically “admissible” errors. The paper reports on three events devoted to morphological tagging, dependency parsing and anaphora resolution, respectively.