LIAAD at SemDeep-5 Challenge: Word-in-Context (WiC)
Table 1: Challenge results at the end of the evaluation period. Bottom results correspond to baselines.
['[BOLD] Submission', '[BOLD] Acc.']
The best system we submitted during the evaluation period of the challenge was a Logistic Regression classifier trained on two similarity features (sim1 and sim2, or contextual and sense-level). Interestingly, the simple approach described in 2.3.1 achieved a competitive performance of 66.3 accuracy, without being trained or fine-tuned on WiC’s data.