CLEF 2017: Multimodal spatial role labeling (mSpRL) task overview

Parisa Kordjamshidi*, Taher Rahgooy, Marie Francine Moens, James Pustejovsky, Umar Manzoor, Kirk Roberts

*Corresponding author for this work

Research output: Chapter in Book/Published conference outputConference publication


The extraction of spatial semantics is important in many real-world applications such as geographical information systems, robotics and navigation, semantic search, etc. Moreover, spatial semantics are the most relevant semantics related to the visualization of language. The goal of multimodal spatial role labeling task is to extract spatial information from free text while exploiting accompanying images. This task is a multimodal extension of spatial role labeling task which has been previously introduced as a semantic evaluation task in the SemEval series. The multimodal aspect of the task makes it appropriate for the CLEF lab series. In this paper, we provide an overview of the task of multimodal spatial role labeling. We describe the task, sub-tasks, corpora, annotations, evaluation metrics, and the results of the baseline and the task participant.

Original languageEnglish
Title of host publicationExperimental IR Meets Multilinguality, Multimodality, and Interaction - 8th International Conference of the CLEF Association, CLEF 2017, Proceedings
EditorsLorraine Goeuriot, Julio Gonzalo, Gareth J.F. Jones, Liadh Kelly, Thomas Mandl, Linda Cappellato, Nicola Ferro, Seamus Lawless
Number of pages10
ISBN (Print)9783319658124
Publication statusPublished - 17 Aug 2017
Event8th International Conference of the CLEF Association, CLEF 2017 - Dublin, Ireland
Duration: 11 Sept 201714 Sept 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10456 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Conference of the CLEF Association, CLEF 2017


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