stanford-core-nlp | Ruby bindings to the Stanford Core NLP tools | Natural Language Processing library
kandi X-RAY | stanford-core-nlp Summary
kandi X-RAY | stanford-core-nlp Summary
Ruby bindings to the Stanford Core NLP tools (English, French, German).
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QUESTION
How can I use Stanford-NLP to lemmatize words or is this even a possibility in coreNLP?
According to this website (https://stanfordnlp.github.io/CoreNLP/human-languages.html) Lemmatization is not an option--but I'm hoping that this is a neglected page that needs to be updated.
Additionally, I've seen related questions but about German: Does Stanford Core NLP support lemmatization for German?
How can I lemmatize spanish words in CoreNLP?
...ANSWER
Answered 2018-Feb-09 at 05:39According to GitHub, this is not functionality that exists in Stanford Core NLP.
QUESTION
On the StanfordCore NLP website there is the following demo:http://nlp.stanford.edu:8080/sentiment/rntnDemo.html
The demo gives a sentence a detailed sentiment score from 0 to 4.
I understand how to get a "positive" or "negative" assessment using command line, similar to this: Screenshot from corenlp.run showing a positive sentiment analysis
I have seen this question already, but I am interested how the analysis shown in the attached screenshot is created. Getting sentiment analysis result using stanford core nlp java code
Is there a way in Stanford CoreNLP to return a score (i.e. 0-4) for a given sentence so show its degree of positivity or negativity?
Thanks!
...ANSWER
Answered 2017-Nov-15 at 04:52There are multiple ways to get that kind of info.
Also I should note that the there is a direct mapping:
"Very negative" = 0 "Negative" = 1 "Neutral" = 2 "Positive" = 3 "Very positive" = 4
Here is a sample command:
QUESTION
I adapted Prof. Mannings code sample from here to read in a file, tokenize, part-of-speech-tag, and lemmatize it.
Now I came across the issue of untokenizable characters, and I would like to use the "untokenizable" option and set it to "noneKeep".
Other questions on StackOverflow explain that I would need to instantiate the tokenizer myself. However, I am not sure how to do that so that the following tasks (POS tagging etc.) are still performed as needed. Can anyone point me in the right direction?
...ANSWER
Answered 2017-May-12 at 22:47Add this to your code:
props.setProperty("tokenize.options", "untokenizable=allKeep");
The 6 options for untokenizable are:
noneDelete, firstDelete, allDelete, noneKeep, firstKeep, allKeep
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