Harnessing the CRF Complexity with Domain-Specific Constraints. The Case of Morphosyntactic Tagging of a Highly Inflected Language

We describe a domain-specific method of adapting conditional random fields (CRFs) to morphosyntactic tagging of highly-inflectional languages. The solution involves extending CRFs with additional, position-wise restrictions on the output domain, which are used to impose consistency between the modeled label sequences and morphosyntactic analysis results both at the level of decoding and, more importantly, in parameters estimation process. We decompose the problem of morphosyntactic disambiguation into two consecutive stages of the context-sensitive morphosyntactic guessing and the disambiguation proper. The division helps in designing well-adjusted, CRF-based methods for both tasks, which in combination constitute Concraft, a highly accurate tagging system for the Polish language available under the 2-clause BSD license. Evaluation on the National Corpus of Polish shows that our solution significantly outperforms other state-of-the-art taggers for Polish – Pantera, WMBT and WCRFT – especially in terms of the accuracy measured with respect to unknown words.