CLEF ProtestNews Lab 2019

Contextualized word embeddings for event sentence detection and event extraction

authored by

Gabriella Skitalinskaya, Jonas Klaff, Maximilian Spliethöver

Abstract

In this work we describe our results achieved in the ProtestNews Lab at CLEF 2019. To tackle the problems of event sentence detection and event extraction we decided to use contextualized string embeddings. The models were trained on a data corpus collected from Indian news sources, but evaluated on data obtained from news sources from other countries as well, such as China. Our models have obtained competitive results and have scored 3rd in the event sentence detection task and 1st in the event extraction task based on average F1-scores for different test datasets.

External Organisation(s)

University of Bremen

Type

Conference article

Journal

CEUR Workshop Proceedings

Volume

2380

ISSN

1613-0073

Publication date

2019

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Computer Science(all)

Electronic version(s)

https://ceur-ws.org/Vol-2380/paper_118.pdf (Access: Closed)