In Experiment 4, using 1,350 frequent terms, we examine the effects of seed lexicon size and specificity and we apply a heuristic based on cognates.
according to our results, translation spotting is more accurate when the seed lexicon contains (5,000) entries from both the medical domain and general language instead of general language words only, but only by a very small margin.