Moreover the quality of the performance of the different feature extraction tools such as AMIRA (for POS tagging and BPC) and MADA (for the morphological features) are optimized for NW data genres, thereby yielding suboptimal performance on the WL genre, leading to more noise than signal for training.
comparing relative performance on this genre, we see a significant jump from the most frequent baseline FreqBaseline (F β=1 =27.66) to the best baseline MLBaseline CRF (F β=1 =55.32).