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

Research Output

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:

31 December 2016
Publication Status:

Published
Publisher

European Language Resources Association
Library of Congress:

QA76 Computer software
Dewey Decimal Classification:

004.2 Systems analysis, design & performance

http://researchrepository.napier.ac.uk/output/169352 <p>Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016). The REAL Corpus: a crowd-sourced corpus of human generated and evaluated spatial references to real-world urban scenes. In <i>10th International Conference on Language Resources and Evaluation (LREC)</i></p>

Citation

Bartie, P., Mackaness, W., Gkatzia, D., & Rieser, V. (2016). 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)