DeepMRT at the NTCIR-14 FinNum Task: A Hybrid Neural Model for Numeral Type Classification in Financial Tweets

Numerals contain much information in the financial domain and thus playing a crucial role in financial analysis processes. In this paper, we focus on the type classification task of numerals in financial tweets and propose a hybrid neural model. A mention model employs a multi-layer perceptron to extract information from target numerals, while a context model utilizes recurrent neural networks to encode preceding and post context separately. Moreover, we present several feature templates to replace inputs like pretrained word vectors, which help the model handle problems caused by sparse numeral embeddings. Experimental results demonstrate that the proposed approach well outperforms baseline methods.