CLEF 2017: Multimodal spatial role labeling task working notes

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

Research output: Contribution to journalConference articlepeer-review


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
Number of pages9
JournalCEUR workshop proceedings
Publication statusPublished - Sept 2017
Event18th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2017 - Dublin, Ireland
Duration: 11 Sept 201714 Sept 2017


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