Derivational Morphological Relations in Word Embeddings

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F19%3A10405586" target="_blank" >RIV/00216208:11320/19:10405586 - isvavai.cz</a>

Result on the web

<a href="https://www.aclweb.org/anthology/W19-4818/" target="_blank" >https://www.aclweb.org/anthology/W19-4818/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.18653/v1/W19-4818" target="_blank" >10.18653/v1/W19-4818</a>

Result language

angličtina

Original language name

Derivational Morphological Relations in Word Embeddings

Original language description

Derivation is a type of a word-formation process which creates new words from existing ones by adding, changing or deleting affixes. In this paper, we explore the potential of word embeddings to identify properties of word derivations in the morphologically rich Czech language. We extract derivational relations between pairs of words from DeriNet, a Czech lexical network, which organizes almost one million Czech lemmas into derivational trees. For each such pair, we compute the difference of the embeddings of the two words, and perform unsupervised clustering of the resulting vectors. Our results show that these clusters largely match manually annotated semantic categories of the derivational relations (e.g. the relation &apos;bake-baker&apos; belongs to category &apos;actor&apos;, and a correct clustering puts it into the same cluster as &apos;govern-governor&apos;).

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

The BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP at ACL 2019

ISBN

978-1-950737-30-7

ISSN

—

e-ISSN

—

Number of pages

8

Pages from-to

173-180

Publisher name

Association for Computational Linguistics

Place of publication

Stroudsburg, PA, USA

Event location

Firenze, Italy

Event date

Aug 1, 2019

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

—