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Showing posts with label WSL. Show all posts
Showing posts with label WSL. Show all posts

Monday, January 6, 2020

Standford NLP Quick Setup on Win10 with WSL

After setting up the Stanford NLP on my PC, I was struggling with how to run it faster. Then I ran into Windows Subsystem for Linux (WSL). I realize that the modification of Stanford NLP is not an option for me. I can use WSL to quickly start an NLP web service and start my work.

I ordered a more powerful VM from Azure and use PowerShell to set up the NLP environment. 

  1. Enable WSL

    Enable-WindowsOptionalFeature -Online -FeatureName Microsoft-Windows-Subsystem-Linux

    It will trigger a reboot if WSL is not enabled
  2. Add Ubuntu disco to WSL

    # download ubuntu 18.04 as save it as Ubuntu.appx at local directory
    Invoke-WebRequest -Uri https://aka.ms/wsl-ubuntu-1804 -OutFile Ubuntu.appx -UseBasicParsing

    # add Ubuntu.appx to WSL
    Add-package Ubuntu.appx
  3. Download Standard NLP zip file and unzip it to the current folder

    # download the Stanford NLP and save the zip file locally as "corenlp.zip"
    Invoke-WebRequest -uri http://nlp.stanford.edu/software/stanford-corenlp-full-2018-10-05.zip -outfile corenlp.zip -UseBasicParsing

    # unzip the corenlp.zip
    Expand-Archive corenlp.zip -DestinationPath .\CoreNlp\
  4. install Java in WSL. Since Stanford NLP does not require Oracle Java, so I use Open Java to make the command shorter

    wsl sudo apt-get update
    wsl sudo apt-get install default-jdk
I go into WSL from PowerShell and launch Stanford NLP from WSL. 

  • go to WSL from Powershell by using "wsl"
  • go to the folder which stores the unzipped Stanford NLP files in step 3
  • run java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer
Open Edge and go to http://localhost:9000/, it will show similar UI like http://corenlp.run.

The PowerShell script used to access the localhost 9000 ports are listed below:

$data = "The quick brown fox jumped over the lazy dog."
$url2 = 'http://localhost:9000/?properties={"annotators":"tokenize,ssplit,pos,lemma,ner, entitymentions,depparse,parse,relation,openie,dcoref,kbp","outputFormat":"json"}'
$r = Invoke-RestMethod -Uri $url2 -Method post -Body $data

The annotators are listed here in case you need it.