VoxEL: A Benchmark Dataset for Multilingual Entity Linking

author: Henry Rosales-Méndez, University of Chile
published: Nov. 22, 2018,   recorded: October 2018,   views: 2427
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

Description

The Entity Linking (EL) task identifies entity mentions in a text corpus and associates them with corresponding entities in a given knowledge base. While traditional EL approaches have largely focused on English texts, current trends are towards language-agnostic or otherwise multilingual approaches that can perform EL over texts in many languages. One of the obstacles to ongoing research on multilingual EL is a scarcity of annotated datasets with the same text in different languages. In this work we thus propose ds: a manually-annotated gold standard for multilingual EL featuring the same text expressed in five European languages. We first motivate and describe the ds dataset, using it to compare the behavior of state of the art EL (multilingual) systems for five different languages, contrasting these results with those obtained using machine translation to English. Overall, our results identify how five state-of-the-art multilingual EL systems compare for various languages, how the results of different languages compare, and further suggest that machine translation of input text to English is now a competitive alternative to dedicated multilingual EL configurations.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: