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

Nominal compounds such as red wine and nut case display a continuum of compositionality,
with varying contributions from the components of the compound to its semantics. This article …

Distributional semantic models (DSMs) are often evaluated on artificial similarity datasets
containing single words or fully compositional phrases. We present a large-scale …

We present a novel method for jointly learning compositional and non-compositional phrase
embeddings by adaptively weighting both types of embeddings using a compositionality …

Statistical association measures (AM) play an important role in the automatic extraction of
collocations and multiword expressions from corpora, but many parameters governing their …

A recent line of work in NLP focuses on the (dis) ability of models to generalise
compositionally for artificial languages. However, when considering natural language tasks …

Phrase embedding aims at representing phrases in a vector space and it is important for the
performance of many NLP tasks. Existing models only regard a phrase as either full …

Implicit discourse relation recognition (IDRR) is to detect and classify relation sense
between two text segments without an explicit connective. Existing neural network models …

Collocation candidate extraction from dependency-annotated corpora has become more
and more mainstream in collocation research over the past years. In most studies, however …

Learning phrase representations has been widely explored in many Natural Language
Processing (NLP) tasks (eg, Sentiment Analysis, Machine Translation) and has shown …