Learning Numeracy: A Simple Yet Effective Number Embedding Approach Using Knowledge Graph
Hanyu Duan, Yi Yang, Kar Yan Tam · 2021
Numeracy plays a key role in natural language understanding.However, existing NLP approaches, either traditional word2vec approach or contextualized transformer-based language models, fail to learn numeracy.As the result, the performance of these models is limited when they are applied to number-intensive applications in clinical and financial domains.In this work, we propose a simple number embedding approach based on knowledge graph.We construct a knowledge graph consisting of number entities and magnitude relations.Knowledge graph embedding method is then applied to obtain number vectors.Our approach is easy to implement, and experiment results on various numeracy-related NLP tasks demonstrate the effectiveness and efficiency of our method.