Natural language parsing with data-driven dependency-based frameworks has received an
increasing amount of attention in recent years, as observed in the shared tasks hosted by …

Dependency grammar is a descriptive and theoretical tradition in linguistics that can be
traced back to antiquity. It has long been influential in the European linguistics tradition and …

Pretrained contextualized embeddings are powerful word representations for structured
prediction tasks. Recent work found that better word representations can be obtained by …

As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality
phrases from a text corpus and has various downstream applications including information …

Multiword expressions (MWEs) are a class of linguistic forms spanning conventional word
boundaries that are both idiosyncratic and pervasive across different languages. The …

Sentiment analysis on Twitter data has attracted much attention recently. In this paper, we
focus on target-dependent Twitter sentiment classification; namely, given a query, we …

This paper describes the neural dependency parser submitted by Stanford to the CoNLL
2017 Shared Task on parsing Universal Dependencies. Our system uses relatively simple …

We describe an open-source toolkit for statistical machine translation whose novel
contributions are (a) support for linguistically motivated factors,(b) confusion network …

In this paper, we make a comparative study of the effectiveness of ensemble technique for
sentiment classification. The ensemble framework is applied to sentiment classification …

Abstract Abstract Meaning Representation (AMR) is a semantic formalism for which a
growing set of annotated examples is available. We introduce the first approach to parse …