It’s not fair to evaluate NLP software on a language it wasn’t designed to process, but I wanted to try it anyway.
The models in the spaCy software library were trained on modern English text and not on Middle English. Nevertheless, spaCy does a pretty good job of parsing Chaucer’s Canterbury Tales, written over 600 years ago. I used the model en_core_web_lg in my little experiment below.
The text I used comes from the prologue:
From every shires ende
of Engelond to Caunterbury they wende
the hooly blisful martir for to seke
that hem hath holpen
whan that they were seeke.
The software correctly identifies, for example, wende (went) and seke (seak) as verbs, and seeke (sick) as an adjective. Overall it does a pretty good job. I imagine it would do worse on Middle English text that differed more from Modern English usage, but so would a contemporary human who doesn’t know Middle English.
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