As Moshe Koppel recently wrote in Mosaic, machine learning has enormous potential for analyzing classical Jewish texts in new ways. Gavriel Fiske reports on a recent example of such an analysis, which ended up finding evidence for what the great rabbi Solomon ben Isaac (Rashi) intuited a millennium ago:
Rabbinic commentators on the Talmud noted in the medieval era that a handful of sections of the great corpus stood out linguistically from the rest. Over generations of scholars, the existence of these so-called “special tractates” was considered to be a clue that could further elucidate how the Talmud was compiled and edited.
Now via modern data analysis, a team of contemporary researchers has shown that these “special tractates” do indeed display a distinct use of language. After feeding nearly the entire talmudic corpus into machine-learning algorithms to parse the Aramaic, they confirmed the theories of Rashi and other medieval scholars.
The clues here come from determining which of the many dialects of Aramaic are used most often. Of particular importance are the differences between the forms of the language spoken by the two main groups who composed the Talmud: Jews of the Galilee and Jews of Mesopotamia:
One of the “special tractates,” Tractate Tamid, which is concerned with the daily sacrifices in the Temple, was found to have a large number of lines flagged by the algorithm, but the team member Noam Eisenstein, an MA student at Tel Aviv University, observed that these lines all dealt with stories about Alexander the Great. If those lines were removed from the equation the tractate would just have normal Jewish Babylonian Aramaic, a possible indicator that those sections were compiled and added from a separate source.
More about: Aramaic, Artificial intelligence, Rashi, Talmud