Concept Tagging for Natural Language Understanding: Two Decadelong Algorithm Development

Code

• github.com/fruttasecca/concept-tagging-with-neural-networks
  OfficialIn paperpytorch★ 0

Abstract

Concept tagging is a type of structured learning needed for natural language understanding (NLU) systems. In this task, meaning labels from a domain ontology are assigned to word sequences. In this paper, we review the algorithms developed over the last twenty five years. We perform a comparative evaluation of generative, discriminative and deep learning methods on two public datasets. We report on the statistical variability performance measurements. The third contribution is the release of a repository of the algorithms, datasets and recipes for NLU evaluation.

Tasks

Reproductions