Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds

Mahmoud El-Haj, Paul Rayson, Scott Piao, Stephen Wattam


Abstract
Creating high-quality wide-coverage multilingual semantic lexicons to support knowledge-based approaches is a challenging time-consuming manual task. This has traditionally been performed by linguistic experts: a slow and expensive process. We present an experiment in which we adapt and evaluate crowdsourcing methods employing native speakers to generate a list of coarse-grained senses under a common multilingual semantic taxonomy for sets of words in six languages. 451 non-experts (including 427 Mechanical Turk workers) and 15 expert participants semantically annotated 250 words manually for Arabic, Chinese, English, Italian, Portuguese and Urdu lexicons. In order to avoid erroneous (spam) crowdsourced results, we used a novel task-specific two-phase filtering process where users were asked to identify synonyms in the target language, and remove erroneous senses.
Anthology ID:
W17-1908
Volume:
Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications
Month:
April
Year:
2017
Address:
Valencia, Spain
Editors:
Jose Camacho-Collados, Mohammad Taher Pilehvar
Venue:
SENSE
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
61–71
Language:
URL:
https://aclanthology.org/W17-1908
DOI:
10.18653/v1/W17-1908
Bibkey:
Cite (ACL):
Mahmoud El-Haj, Paul Rayson, Scott Piao, and Stephen Wattam. 2017. Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds. In Proceedings of the 1st Workshop on Sense, Concept and Entity Representations and their Applications, pages 61–71, Valencia, Spain. Association for Computational Linguistics.
Cite (Informal):
Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds (El-Haj et al., SENSE 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-1908.pdf