This project focuses on a modification of a greedy transition based dependency parser. Typically a Part-Of-Speech (POS) tagger models a probability distribution over all the possible tags for each word in the given sentence and chooses one as its best guess. This is then pass on to the parser which uses this information to build a parse tree. The current state of the art for POS tagging is about 97% word accuracy, which seems high but results in a around 56% sentence accuracy. Small errors at the POS tagging phase can lead to large errors down the NLP pipeline and transition based parsers are particularity sensitive to these types of mistakes. A maximum entropy Markov model was trained as a POS multi-tagger passing more than its 1-best guess to the parser which was thought could make a better decision when committing to a parse for the sentence. This has been shown to give improved accuracy in other parsing approaches. We shown there is a correlation between tagging ambiguity and parsers accuracy and in fact the higher the average tags per word the higher the accuracy.
EasyPS is a simple and easy-to-use personal statement LaTeX framework. This solves the problem of messy and duplicated TeX files when writing personal statements for multiple universities. For more information, go to: https://github.com/salfaris/EasyPS.
A bare-bones template for writing Linguistics papers at Pomona College. It may also be useful to linguists/linguistics students at other places. Includes links to our quick reference guide as well, which has more detailed instructions on formatting for linguistics papers.
I made this template based off my successful Goldwater Scholarship research essay in 2019. If nothing about the formatting has changed since then, it should be good to go. You can find my completed essay here: https://www.overleaf.com/latex/templates/goldwater-scholarship-research-essay-example/fnmwcnpvxgbg