Mingyu WAN author Kathleen Ahrens author Emmanuele Chersoni author Menghan Jiang author Qi Su author Rong Xiang author Chu-Ren Huang author 2020-jul text Association for Computational Linguistics Online conference publication This paper reports a linguistically-enriched method of detecting token-level metaphors for the second shared task on Metaphor Detection. We participate in all four phases of competition with both datasets, i.e. Verbs and AllPOS on the VUA and the TOFEL datasets. We use the modality exclusivity and embodiment norms for constructing a conceptual representation of the nodes and the context. Our system obtains an F-score of 0.652 for the VUA Verbs track, which is 5% higher than the strong baselines. The experimental results across models and datasets indicate the salient contribution of using modality exclusivity and modality shift information for predicting metaphoricity. wan-etal-2020-using https://www.aclweb.org/anthology/2020.figlang-1.16 2020-jul 104 109