Lexical Sememe Prediction using Dictionary Definitions by Capturing Local Semantic Correspondence
Table 4: Sememe prediction MAPs for words with different frequency ranges. The numbers of words in the four ranges are 31481, 10714, 4528 and 1660 respectively.
['Word Frequency', '≥5000', '500-5000', '50-500', '≤50']
SCorP(+SE,TW) produces the best performance in all the word frequency ranges, which manifests its remarkable robustness. CSP, which relies heavily on word embeddings, suffers a sharp performance drop when faced with low-frequency words (word frequency less than 50), although they perform acceptably on high-frequency words. LD+Seq2Seq is less affected by word frequencies, but it badly lags behind other models on whichever word frequency range.