Adapting a constituency parser to user-generated content in polish opinion mining

Abstract

The paper focuses on the adjustment of NLP tools for Polish, e.g., morphological analyzers and parsers, to user-generated content (UGC). The authors discuss two rule-based techniques applied to improve their efficiency: pre-processing (text normalization) and parser adaptation (modified segmentation and parsing rules). A new solution to handle OOVs based on inflectional translation is also offered.