Coreference resolution for Russian: the impact of semantic features
This paper presents the results of our experiments on building a general coreference resolution system for Russian. The main aim of those experiments was to set a baseline for this task for Russian using the standard set of features developed and tested for coreference resolution systems created for other languages. We propose several baseline systems, both rule-based and ML-based. We show that adding some semantic information is crucial for the task and even the small amount of data can improve the overall result. We show that different types of semantic resources affect the performance differently and sometimes more does not imply better.