Intelligent Translation Memory Matching and Retrieval with Sentence Encoders
Table 8: Result comparison between Okapi and the Universal Sentence Encoder for each partition after performing NER. The Fuzzy score column represents each partition. The Okapi column shows the average METEOR score between the matches provided by the Okapi and the actual translations in that partition. The USE column shows the average METEOR score between the matches provided by the Universal Sentence Encoder and the actual translations in that partition. The Amount column shows the number of sentences in each partition. Bold shows the best result for that partition
['[BOLD] Fuzzy score', '[BOLD] Okapi', '[BOLD] USE', '[BOLD] Amount']
However for the cases where the fuzzy match score is below 0.8 the Universal Sentence Encoder seems to be better than Okapi. After performing NER, the results of the Universal Sentence Encoder improved significantly in most of the partitions: specially in 0.6-0.8 partition.