POS Tagging for German: how important is the Right Context?

Part-of-Speech tagging is generally performed by Markov models, based on bigram or trigram models. While Markov models have a strong concentration on the left context of a word, many languages require the inclusion of right context for correct disambiguation. We show for German that the best results are reached by a combination of left and right context. If only left context is available, then changing the direction of analysis and going from right to left improves the results. In a version of MBT (Daelemans et al., 1996) with default parameter settings, the inclusion of the right context improved POS tagging accuracy from 94.00% to 96.08%, thus corroborating our hypothesis. The version with optimized parameters reaches 96.73%.

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Steliana Ivanova, Sandra Kuebler
• Keywords: Education, LREC 2008, Markov Models, Part-of-speech Tagging, Right Context