We present an extension to incremental shift-reduce parsing that handles discontinuous constituents, using a linear classifier and beam search. We achieve very high parsing speed...
Automatic timeline summarization (TLS) generates precise, dated overviews over (often prolonged) events, such as wars or economic crises. One subtask of TLS selects the most impor...
Computing pairwise word semantic similarity is widely used and serves as a building block in many tasks in NLP. In this paper, we explore the embedding of the shortest-path metric...
Labeled data is not readily available for many natural language domains, and it typically requires expensive human effort with considerable domain knowledge to produce a set of la...
An elementary way of using language is to refer to objects. Often, these objects are physically present in the shared environment and reference is done via mention of perceivable ...
We propose a language production model that uses dynamic discourse information to account for speakers’ choices of referring expressions. Our model extends previous rational spe...
Naho Orita, Eliana Vornov, Naomi Feldman, Hal Daum...
Neural machine translation, a recently proposed approach to machine translation based purely on neural networks, has shown promising results compared to the existing approaches su...
This paper describes a parsing model that combines the exact dynamic programming of CRF parsing with the rich nonlinear featurization of neural net approaches. Our model is struct...