Task-Oriented Learning of Word Embeddings for Semantic Relation Classification
Table 4: Cross-validation results for ablation tests.
['[BOLD] gn', '[BOLD] gin', '[BOLD] g′in', '[BOLD] gn, [BOLD] gin', '[BOLD] gn, [BOLD] gin, [BOLD] gout']
We also provide a score using a simplified version of gin, where the feature vector g′in is computed by averaging the word embeddings [W(wini);~W(wini)] of the words between the noun pairs. This feature vector g′in then serves as a bag-of-words feature. The difference between the scores of gin and g′in shows the effectiveness of our averaged n-gram embeddings.