Word class flexibility: A deep contextualized approach

09/19/2020
by   Bai Li, et al.
0

Word class flexibility refers to the phenomenon whereby a single word form is used across different grammatical categories. Extensive work in linguistic typology has sought to characterize word class flexibility across languages, but quantifying this phenomenon accurately and at scale has been fraught with difficulties. We propose a principled methodology to explore regularity in word class flexibility. Our method builds on recent work in contextualized word embeddings to quantify semantic shift between word classes (e.g., noun-to-verb, verb-to-noun), and we apply this method to 37 languages. We find that contextualized embeddings not only capture human judgment of class variation within words in English, but also uncover shared tendencies in class flexibility across languages. Specifically, we find greater semantic variation when flexible lemmas are used in their dominant word class, supporting the view that word class flexibility is a directional process. Our work highlights the utility of deep contextualized models in linguistic typology.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/06/2020

ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades

Word embeddings learn implicit biases from linguistic regularities captu...
research
04/30/2020

Analyzing the Surprising Variability in Word Embedding Stability Across Languages

Word embeddings are powerful representations that form the foundation of...
research
04/06/2017

The Interplay of Semantics and Morphology in Word Embeddings

We explore the ability of word embeddings to capture both semantic and m...
research
01/13/2022

Compressing Word Embeddings Using Syllables

This work examines the possibility of using syllable embeddings, instead...
research
10/04/2019

DialectGram: Detecting Dialectal Variation at Multiple Geographic Resolutions

Several computational models have been developed to detect and analyze d...
research
10/07/2020

Analogies minus analogy test: measuring regularities in word embeddings

Vector space models of words have long been claimed to capture linguisti...
research
04/29/2017

Extending and Improving Wordnet via Unsupervised Word Embeddings

This work presents an unsupervised approach for improving WordNet that b...

Please sign up or login with your details

Forgot password? Click here to reset