Research Output

The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes

  We present a newly crowd-sourced data set of natural language references to objects anchored in complex urban scenes (In short: The REAL Corpus – Referring Expressions Anchored Language). The REAL corpus contains a collection of images of real-world urban
scenes together with verbal descriptions of target objects generated by humans, paired with data on how successful other people were
able to identify the same object based on these descriptions. In total, the corpus contains 32 images with on average 27 descriptions per image and 3 verifications for each description. In addition, the corpus is annotated with a variety of linguistically motivated features.
The paper highlights issues posed by collecting data using crowd-sourcing with an unrestricted input format, as well as using real-world urban scenes. The corpus will be released via the ELRA repository as part of this submission.

  • Date:

    30 November 2015

  • Publication Status:

    Published

  • Publisher

    European Language Resources Association

  • Library of Congress:

    QA76 Computer software

  • Dewey Decimal Classification:

    004.2 Systems analysis, design & performance

Citation

Bartie, P., Mackaness, W., Gkatzia, D. & Rieser, V. (2015). The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In 10th International Conference on Language Resources and Evaluation (LREC)ISBN 978-2-9517408-9-1

Authors

Keywords

Real-world urban spaces; spatial references; crowd sourcing;

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