Exploiting BERT for End-to-End Aspect-based Sentiment Analysis The work described in this paper is substantially supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project Code: 14204418).
Table 2: Main results. The symbol ♮ denotes the numbers are officially reported ones. The results with ♯ are retrieved from Li et al. (2019a).
['[EMPTY]', 'Model', 'LAPTOP', 'LAPTOP', 'LAPTOP', 'REST', 'REST', 'REST']
It is also observed that slightly more powerful E2E-ABSA layers lead to much better performance, verifying the postulation that incorporating context helps to sequence modeling.