CLEF ProtestNews Lab 2019

Contextualized word embeddings for event sentence detection and event extraction

verfasst von

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.

Externe Organisation(en)

Universität Bremen

Typ

Konferenzaufsatz in Fachzeitschrift

Journal

CEUR Workshop Proceedings

Band

2380

ISSN

1613-0073

Publikationsdatum

2019

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Informatik (insg.)

Elektronische Version(en)

https://ceur-ws.org/Vol-2380/paper_118.pdf (Zugang: Geschlossen)