syntaxnet

I downloaded and installed SyntaxNet following Syntax official documentation on Github . following the documentation (annotating corpus) I tried to read a .conll file named wj.conll by SyntaxNet and write the results in wj-tagged.conll but I could not. My questions are: does SyntaxNet always reads .conll files? (not .txt files?). I got a bit confused as I knew SyntaxNet reads .conll file for training and testing process but I am a bit suspicious that it is necessary to convert a .txt file to .conll file in order to have their Part Of Speach and Dependancy Parsing. How can I make SyntaxNet

having downloaded and trained SyntaxNet , I am trying to write a program that can open new/existed files, for example AutoCAD files, and save the files in an specific directory by analyzing the text: open LibreOffice file X . considering the output of SyntaxNet as: echo "save AUTOCAD file X in directory Y" | ./test.sh > output.txt Input: save AUTOCAD file X in directory Y Parse: save VB ROOT +-- X NNP dobj | +-- file NN compound | +-- AUTOCAD CD nummod +-- directory NN nmod +-- in IN case +-- Y CD nummod First I thought about changing the parsed text to XML format then parse the XML file with

How do you get a dependency parse (not syntax tree) output from SyntaxNet ( https://github.com/tensorflow/models/tree/master/syntaxnet ) ? I see a description of dependency parsing...a description of how to train a model, but not how to get dependency parse output. Does SyntaxNet (Specifically the Parsey McParseface model) even do dependency parsing out of the box? Passing --arg_prefix brain_parser to the parser_eval.py should do the trick. But this requires the tagged output to be fed as input. Here's an example where the first pass tags the words and the second pass resolves dependencies: