stanford-segmenter | chinese parsing segmentation of words | Machine Learning library
kandi X-RAY | stanford-segmenter Summary
kandi X-RAY | stanford-segmenter Summary
chinese parsing segmentation of words. to load in intellij idea, run gradlew idea on any OS and then import (no need to install gradle but must have jdk installed). to load in eclipse, run gradlew eclipse on any OS (no need to install gradle but must have jdk installed). to build the jar, run gradlew assemble.
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Top functions reviewed by kandi - BETA
- Transforms the given subtree to its original tree .
- Return a collection of features for the feature c .
- Sets the option to use .
- moves the cursor to the next state
- Translates a string .
- Internal helper method to print the tree .
- transforms a tree t into CCN
- Creates a counter from a map of numbers .
- Return a collection of features features for c .
- Collapses three words in a list of syntactic dependencies .
stanford-segmenter Key Features
stanford-segmenter Examples and Code Snippets
Community Discussions
Trending Discussions on stanford-segmenter
QUESTION
I have setup the environment variables as instructed by the official NLTK wiki. I run into the following error in my very first example. Here are the codes:
...ANSWER
Answered 2017-Sep-29 at 07:58For some reason list2cmdline(args)
in subprocess.py
is returning [None]
, and it is not being handled properly. I would guess that it's a problem with the java()
call in stanford_segmenter.py
.
From here you can see that the code was updated to require Java 8 back in 2014. If your Java version is lower than this, it could be the problem.
QUESTION
I'm trying to use the Stanford Segementer bit from the NLTK Tokenize package. However, I run into issues just trying to use the basic test set. Running the following:
...ANSWER
Answered 2017-Oct-17 at 02:45Note: This solution would only work for:
- NLTK v3.2.5 (v3.2.6 would have an even simpler interface)
- Stanford CoreNLP (version >= 2016-10-31)
First you have to get Java 8 properly installed first and if Stanford CoreNLP works on command line, the Stanford CoreNLP API in NLTK v3.2.5 is as follows.
Note: You have to start the CoreNLP server in terminal BEFORE using the new CoreNLP API in NLTK.
EnglishIn terminal:
QUESTION
I'm using the Stanford POS tagger 3.7.0 in a Java project that also uses the Jena RDF API. Jena requires slf4j-api-1.7.12.jar and slf4j-log4j12-1.7.12.jar, but when trying to call the POS tagger having those jars in the classpath I get the following error:
...ANSWER
Answered 2017-Mar-20 at 21:29I think the best solution is to just use the full Stanford CoreNLP 3.7.0 release which won't have this issue but will have all the POS tagging functionality.
The full download is available here:
http://stanfordnlp.github.io/CoreNLP/download.html
This issue should be resolved in the standalone distributions for Stanford CoreNLP 3.8.0 which we'll try to release in the early summer.
QUESTION
I've set up a nltk
and stanford
environment, and nltk
and stanford
jars has downloaded, the program with nltk
was ok, but I had a trouble with stanford
segmenter. just make a simple program via stanford
segmenter, I got a error is Could not find SLF4J
in your classpath, although I had exported all jars including slf4j-api.jar
. Detail as follows
- Python3.5 NLTK 3.2.2 Standford jars 3.7
- OS: Centos
environment variable:
...
ANSWER
Answered 2017-Mar-13 at 08:13With the current code base if you have the slf4j-api.jar in your CLASSPATH and run the 3.7.0 segmenter you will get this error. I'm going to push a code change to fix this but for the time being if you remove the slf4j-api.jar from the CLASSPATH this error should go away.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install stanford-segmenter
You can use stanford-segmenter like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the stanford-segmenter component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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