A3 studies semantic composition models for German and English phrases, focusing on adjective-noun phrases and prepositional phrases. The computational modelling will use distributional word representations and deep learning techniques, in particular recurrent neural networks (RNN).
Of special interest is the relation between composition and parsing. Existing composition models integrated into parsers are usually trained together with the parser in a supervised manner, typically only on treebank data. In contrast, our approach uses unsupervised learning to train stand-alone composition models from large parsed corpora. The semantic phrase representations built by the pre-trained composition models can then be integrated into the parser to improve parsing accuracy.
The composition models will be evaluated on several tasks including semantic relation classification, PP-attachment disambiguation, recognising textual entailment and text-to-image retrieval.
Associated to the Project:
Seminar für Sprachwissenschaft
Former Staff, Associates and Student Assistants :
Dr. Heike Telljohann