BCWS: Bilingual Contextual Word Similarity
This dataset addresses the problem of cross-lingual sense representation for researchers in natural language processing, enabling progress from monolingual to multilingual AI understanding, though it is incremental as it builds on existing monolingual datasets.
The authors introduced the first dataset for evaluating English-Chinese bilingual contextual word similarity, called BCWS, consisting of 2,091 word pairs with human-annotated similarity scores and sentential contexts, and established baselines for benchmarking.
This paper introduces the first dataset for evaluating English-Chinese Bilingual Contextual Word Similarity, namely BCWS (https://github.com/MiuLab/BCWS). The dataset consists of 2,091 English-Chinese word pairs with the corresponding sentential contexts and their similarity scores annotated by the human. Our annotated dataset has higher consistency compared to other similar datasets. We establish several baselines for the bilingual embedding task to benchmark the experiments. Modeling cross-lingual sense representations as provided in this dataset has the potential of moving artificial intelligence from monolingual understanding towards multilingual understanding.