A “lemma-based search” identifies the co-occurrence of the same word with different inflections, and this is the basis for version 3.0 of the Tesserae software. In a benchmark test of Pharsalia 1 vs. Aeneid, 55% of parallels previously noted by commentators were retrieved by lemma-based search.
Previous posts have discussed the method of generating metonym (synonym, antonym, hyponym, etc.) dictionaries through the application of topic modeling. In order to capture more of our target intertexts, we worked to generate the most accurate possible metonym dictionary, then combined it with lemmatization in order to simultaneously capture different inflections of the same word and metonyms of that word.
In a repeat of the benchmark test above, the new ‘synonym + lemma’ feature retrieved commentator parallels at a rate of 68% (other search settings remained the same).
