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If we take an existing supervised NLP sys- tem, a simple and general way to improve accuracy is to use unsupervised word representations as extra word features. We evaluate Brown …...

This paper describes our participation on Task 7 of SemEval 2014, which fo- cused on the recognition and disambigua- tion of medical concepts. We used an adapted version of the …...

Word embeddings — distributed word representations that can be learned from unlabelled data — have been shown to have high utility in many natural language processing applications. In this paper, …...

This paper presents a detailed compar- ative framework for assessing the use- fulness of unsupervised word representa- tions for identifying so-called implicit dis- course relations. Specifically, we compare standard one-hot …...

Named entity recognition (NER) systems trained on newswire perform very badly when tested on Twitter. Signals that were reliable in copy-edited text disappear almost entirely in Twitter’s informal chatter, requiring …...

As more historical texts are digitized, there is interest in applying natural language pro- cessing tools to these archives. However, the performance of these tools is often unsatisfac- tory, due …...

AbstractUnsupervised part of speech (POS) tagging is often framed as a clustering problem, but practical taggers need to ground their clusters as well. Grounding generally requires reference labeled data, a …...