Mova · papers by stage
text → tokens
Splitting the text into words with their part of speech, lemma and features: the tagger and its lexicon. The 3 works of Mova's own list that this stage uses; measured marks a work whose effect Mova measured in its own experiments (1 here). Each title opens our card: the summary, how Mova uses the work, its references and who cites it. What the stage does is on Mova's pipeline page; every stage is on the main list.
- TnT – A Statistical Part-of-Speech TaggermeasuredThorsten Brants · 2000
What Mova took:
en/src/tag.rs— a direct reimplementation: trigram Markov model over tag classes with a dense transition table, deleted-interpolation smoothing, a word-to-tags lexicon for known words, and suffix models… - Part-of-Speech Tagging Guidelines for the Penn Treebank Project (3rd Revision)Beatrice Santorini · 1990
What Mova took:
en/seeds/— the English grammar seeds (short declarative rule notes with conditions, exceptions, examples and sources) cite the guidelines as the authority for PTB tag decisions; about 43 seed files reference it, mostly under… - A Good Part-of-Speech Tagger in about 200 Lines of PythonMatthew Honnibal · 2013
What Mova took:
en/src/ptag.rs— the Penn Treebank tagger follows this recipe: an averaged perceptron (Collins 2002) with a greedy left-to-right pass, as described in the article.