COS960: A Chinese Word Similarity Dataset of 960 Word Pairs

06/01/2019
by   Junjie Huang, et al.
0

Word similarity computation is a widely recognized task in the field of lexical semantics. Most proposed tasks test on similarity of word pairs of single morpheme, while few works focus on words of two morphemes or more morphemes. In this work, we propose COS960, a benchmark dataset with 960 pairs of Chinese wOrd Similarity, where all the words have two morphemes in three Part of Speech (POS) tags with their human annotated similarity rather than relatedness. We give a detailed description of dataset construction and annotation process, and test on a range of word embedding models. The dataset of this paper can be obtained from https://github.com/thunlp/COS960.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/21/2018

BCWS: Bilingual Contextual Word Similarity

This paper introduces the first dataset for evaluating English-Chinese B...
research
03/17/2017

Construction of a Japanese Word Similarity Dataset

An evaluation of distributed word representation is generally conducted ...
research
07/12/2017

A Critique of a Critique of Word Similarity Datasets: Sanity Check or Unnecessary Confusion?

Critical evaluation of word similarity datasets is very important for co...
research
08/28/2018

WiC: 10,000 Example Pairs for Evaluating Context-Sensitive Representations

By design, word embeddings are unable to model the dynamic nature of wor...
research
10/14/2020

Chinese Lexical Simplification

Lexical simplification has attracted much attention in many languages, w...
research
05/15/2018

Unsupervised Learning of Style-sensitive Word Vectors

This paper presents the first study aimed at capturing stylistic similar...
research
09/17/2019

Semantic Relatedness Based Re-ranker for Text Spotting

Applications such as textual entailment, plagiarism detection or documen...

Please sign up or login with your details

Forgot password? Click here to reset