Parse-tree paths are commonly used to incorporate information from syntactic parses into NLP systems. These systems typically treat the paths as atomic (or nearly atomic) features...
We propose the use of regular tree grammars (RTGs) as a formalism for the underspecified processing of scope ambiguities. By applying standard results on RTGs, we obtain a novel a...
In adding syntax to statistical MT, there is a tradeoff between taking advantage of linguistic analysis, versus allowing the model to exploit linguistically unmotivated mappings l...
We propose an automatic machine translation (MT) evaluation metric that calculates a similarity score (based on precision and recall) of a pair of sentences. Unlike most metrics, ...
Statistical machine learning methods are employed to train a Named Entity Recognizer from annotated data. Methods like Maximum Entropy and Conditional Random Fields make use of fe...
Traditional wisdom holds that once documents are turned into bag-of-words (unigram count) vectors, word orders are completely lost. We introduce an approach that, perhaps surprisi...
Xiaojin Zhu, Andrew B. Goldberg, Michael Rabbat, R...
Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tail...
This paper is concerned with the problem of question search. In question search, given a question as query, we are to return questions semantically equivalent or close to the quer...
Previous studies evaluate simulated dialog corpora using evaluation measures which can be automatically extracted from the dialog systems' logs. However, the validity of thes...
For centuries, the deep connection between languages has brought about major discoveries about human communication. In this paper we investigate how this powerful source of inform...