Белгісіз деректер

In this paper we report an empirical study on semi-supervised Chinese word segmenta- tion using co-training. We utilize two seg- menters: 1) a word-based segmenter lever- aging a word-level language …...

State-of-the-art semantic role labelling systems require large annotated corpora to achieve full performance. Unfortunately, such corpora are expensive to produce and often do not generalize well across do- mains. Even …...

AbstractMannual annotation for dependency parsing is both labourious and time costly, resulting in the difficulty to learn practical dependency parsers for many languages due to the lack of labelled training …...

AbstractIn this paper, we propose a meta-learning based semi-supervised explicit dialogue state tracker (SEDST) for neural dialogue generation, denoted as MEDST. Our main motivation is to further bridge the chasm …...