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Yayın Chunking in Turkish with conditional random fields(Springer-Verlag, 2015-04-14) Yıldız, Olcay Taner; Solak, Ercan; Ehsani, Razieh; Görgün, OnurIn this paper, we report our work on chunking in Turkish. We used the data that we generated by manually translating a subset of the Penn Treebank. We exploited the already available tags in the trees to automatically identify and label chunks in their Turkish translations. We used conditional random fields (CRF) to train a model over the annotated data. We report our results on different levels of chunk resolution.Yayın The expressions of spatial relations during interaction in American sign language, Croatian sign language, and Turkish sign language(Versita, 2012-11) Arik, EnginSigners use their body and the space in front of them iconically. Does iconicity lead to the same mapping strategies in construing space during interaction across sign languages? The present study addressed this question by conducting an experimental study on basic static and motion event descriptions during interaction (describer input and addressee re-signing/retelling) in American Sign Language, Croatian Sign Language, and Turkish Sign Language. I found that the three sign languages are similar in using classifier predicates of location, orientation, and movement, predominantly employing an egocentric (viewer) perspective but also a non-egocentric perspective, and using similar mapping strategies regardless of interlocutor positions. However, these three sign languages differ from each other in the effects of location and orientation of the objects in pictures and movies, the descriptions of picture (states) vs. movie (motion events), and describer input vs. addressee retellings in their mapping strategies. This study contributes to our knowledge of how the expressions of spatial relations are conveyed in natural human language.
