State-of-the-art natural language processing (NLP) models are trained on massive training
corpora, and report a superlative performance on evaluation datasets. This survey delves …

Neural networks have shown promising results for relation extraction. State-of-the-art
models cast the task as an end-to-end problem, solved incrementally using a local classifier …

We study the problem of analyzing tweets with Universal Dependencies. We extend the UD
guidelines to cover special constructions in tweets that affect tokenization, part-of-speech …

Due to the presence of both Twitter-specific conventions and non-standard and dialectal
language, Twitter presents a significant parsing challenge to current dependency parsing …

Code-switching is a phenomenon of mixing grammatical structures of two or more
languages under varied social constraints. The code-switching data differ so radically from …

Due to the spread of social media-based applications and the challenges posed by the
treatment of social media texts in NLP tools, tailored approaches and ad hoc resources are …

Natural language processing (NLP) systems are now ubiquitous. Yet the benefits of these
language technologies do not accrue evenly to all users, and indeed they can be harmful; …

JamPatoisNLI provides the first dataset for natural language inference in a creole language,
Jamaican Patois. Many of the most-spoken low-resource languages are creoles. These …

Language technologies should be judged on their usefulness in real-world use cases. An
often overlooked aspect in natural language processing (NLP) research and evaluation is …

Treebank translation is a promising method for cross-lingual transfer of syntactic
dependency knowledge. The basic idea is to map dependency arcs from a source treebank …