Natural Language Processing (NLP)

The Natural Language Processing (NLP) group develops methods, algorithms, and tools for the automatic analysis of natural language. The group focuses on questions related to processing, understanding and generating discourse. It works on coreference resolution with a particular focus on appropriate representations for the task. It develops models of local coherence, most recently an unsupervised, graph-based version of the entity grid with applications in text generation, assessing readability and automatic summarization. The group is also interested in word sense disambiguation and its relations to discourse processing.



New research training group funded by DFG: AIPHES (Adaptive Information Processing from Heterogeneous Sources). This is a collaboration between the CS Department at the Technical University of Darmstadt, the Institute for Computational Linguistics at the University of Heidelberg and the NLP Group at HITS. We’ll focus on concept disambiguation in relation with discourse processing and…


EMNLP 2014

Two long papers accepted at EMNLP ’14: Yufang Hou, Katja Markert and Michael Strube: A rule-based system for end-to-end bridging resolution, and Sebastian Martschat and Michael Strube: Recall error analysis for coreference resolution.