Published October 31, 2021
| Version 1
Dataset
Open
Data and source code for Automatic generation of a large dictionary with concreteness/abstractness ratings based on a small human dictionary
Authors/Creators
- 1. Innopolis University
- 2. Kazan Federal University
Description
We present a method for automatic ranking concreteness of words and propose an approach to significantly decrease amount of expert assessment. The method has been evaluated on a large test set for English. The quality of the constructed dictionaries is comparable to the expert ones. The correlation between predicted and expert ratings is higher comparing to the state-of-the-art methods.
Files
paper_source_code_and_data.zip
Files
(5.9 MB)
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md5:1537c3934da5ee04bf5b5e4618d98d0b
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