  Morphological analysis (MA) and lexical normalization (LN) are both important
tasks for Japanese user-generated text (UGT). To evaluate and compare different
MA/LN systems, we have constructed a publicly available Japanese UGT corpus.
Our corpus comprises 929 sentences annotated with morphological and
normalization information, along with category information we classified for
frequent UGT-specific phenomena. Experiments on the corpus demonstrated the low
performance of existing MA/LN methods for non-general words and non-standard
forms, indicating that the corpus would be a challenging benchmark for further
research on UGT.
