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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.

Swedish version of the letter template, according to the School of Electrical Engineering of Swedish Royal Institute of Technology (Kungliga Tekniska Hogskolan, KTH) rules. This template was originally published on ShareLaTeX and subsequently moved to Overleaf in October 2019.

My guide to logarithms.

Plantilla para desarrollo de reporte científico básico, orientada al curso de Física Mecánica de la carrera de Ingeniería en Sonido de la Universidad de Chile

English version of the letter template, according to the School of Electrical Engineering of Swedish Royal Institute of Technology (Kungliga Tekniska Hogskolan, KTH) rules. This template was originally published on ShareLaTeX and subsequently moved to Overleaf in October 2019.

Unofficial ARPA-FVG template for technical reports

This handout template is developed by the Tufte-LaTeX Developers, designed to produce handouts according to the style of Edward R. Tufte. This style is characterized by narrow main-text column and wide right margin (containing references, notes, table and figure captions, even small figures), giving the light, clean, and elegant look. For further information, see https://tufte-latex.github.io/tufte-latex/. This template was originally published on ShareLaTeX and subsequently moved to Overleaf in October 2019.

Title Page for SUAI (Saint-Petersburg State University of Aerospace Instrumentation) students

Não sou o autor deste template, somente fiz o upload do modelo que o professor Senger me passou para uso no Overleaf. Se houver um template melhor ou alguma sugestão de melhoria por favor me contate por e-mail: ribas.jonathan@gmail.com.