Integrating Vision and Language Datasets to Measure Word Concreteness

IJCNLP 2017  ·  Gitit Kehat, James Pustejovsky ·

We present and take advantage of the inherent visualizability properties of words in visual corpora (the textual components of vision-language datasets) to compute concreteness scores for words. Our simple method does not require hand-annotated concreteness score lists for training, and yields state-of-the-art results when evaluated against concreteness scores lists and previously derived scores, as well as when used for metaphor detection.

PDF Abstract IJCNLP 2017 PDF IJCNLP 2017 Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods


No methods listed for this paper. Add relevant methods here