Linguistic typology aims to capture structural and semantic variation across the world's
languages. A large-scale typology could provide excellent guidance for multilingual Natural …

Many NLP tasks have at their core a subtask of extracting the dependencies—who did what
to whom—from natural language sentences. This task can be understood as the inverse of …

Languages differ in how they divide up the world into concepts and words; eg, in contrast to
English, Swahili has a single concept forbelly'andwomb'. We investigate these differences in …

In recent years linguistic typology, which classifies the world's languages according to their
functional and structural properties, has been widely used to support multilingual NLP. While …

Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of
both Natural Language Understanding (NLU) and Natural Language Generation (NLG) …

This paper explores the ways in which the field of natural language processing (NLP) can
and does benefit from work in linguistic typology. I describe the recent increase in interest in …

The idea that being bilingual benefits one's cognitive development and performance has
been greatly challenged over the last years. If such an effect exists, as some studies …

Linguists and psychologists have long been studying cross-linguistic transfer, the influence
of native language properties on linguistic performance in a foreign language. In this work …

We propose to bring together two kinds of linguistic resources—interlinear glossed text (IGT)
and a language-independent precision grammar resource—to automatically create …

Most natural language models and tools are restricted to one language, typically English.
For researchers in the behavioral sciences investigating languages other than English, and …