Published October 31, 2021 | Version 1

Data and source code for Automatic generation of a large dictionary with concreteness/abstractness ratings based on a small human dictionary

  • 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.

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paper_source_code_and_data.zip

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