stanford-ner | simple Node.js wrapper

by vchatterji TypeScript Version: 1.0.0 License: No License

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | stanford-ner Summary

stanford-ner is a TypeScript library. stanford-ner has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

For the sake of simplicity, I have bundled stanford-ner-2015-12-09, but you can use a later version by specifying the (absolute) path in the options.

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Quality

Security

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Support

stanford-ner has a low active ecosystem.

It has 14 star(s) with 8 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 2 have been closed. On average issues are closed in 17 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of stanford-ner is 1.0.0

Quality

stanford-ner has no bugs reported.

Security

stanford-ner has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

stanford-ner does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

stanford-ner releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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stanford-ner Key Features

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stanford-ner Examples and Code Snippets

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Community Discussions

Trending Discussions on stanford-ner

Extract information from a string - What technique in ML can solve

NLTK unable to find java.exe (spontaneous path reduction)

Customized StanfordNER

QUESTION

Extract information from a string - What technique in ML can solve

Asked 2021-Mar-20 at 10:07

I would like to know what kind of technique in Machine Learning domain can solve the problem below? (For example: Classification, CNN, RNN, etc.)

Problem Description:

User would input a string, and I would like to decompose the string to get the information I want. For example:

User inputs "R21TCCCUSISS", and after code decomposing, then I got the information: "R21" is product type, "TCC" is batch number, "CUSISS" is the place of origin
User inputs "TT3SUAWXCCAT", and after code decomposing, then I got the information: "TT3S" is product type, "SUAW" is batch number, "X" is a wrong character that user input , and "CCAT" is the place of origin

There are not fix string length in product type, batch number, and place of origin. Like product type may be "R21" or "TT3S", meaning that product type may comprise 2 or 3 character.

Also sometimes the string may contain wrong input information, like the "X" in example 2 shown above.

I’ve tried to find related solution, but what I got the most related is this one: https://github.com/philipperemy/Stanford-NER-Python

However, the string I got is not a sentence. A sentence comprises spaces & grammar, but the string I got doesn’t fit this situation.

...

ANSWER

Answered 2021-Mar-20 at 10:07

Your problem is not reasonnably solved with any ML since you have a defined list of product type etc, since there may not be any actual simple logic, and since typically you are never working in the continuum (vector space etc). The purpose of ML is to build a regression function from few pieces of data and hope/expect a good generalisation (the regression fits all the unseen examples, past present and future).

Basically you are trying to reverse engineer the input grammar and generation (which was done by an algorithm, including possibly a random number generator). But in order to assert that your classifier function is working properly you need all your data to be also groundtruth, which breaks the ML principle.

You want to list all your list of defined product types (ground truth), and scatter bits of your input (with or without a regex pattern) into different types (batch number, place of origin). The "learning" is actually building a function (or few, one per type), element by element, which is filling a map (c++) or a dictionary (c#), and using it to parse the input.

Source https://stackoverflow.com/questions/66718436

QUESTION

NLTK unable to find java.exe (spontaneous path reduction)

Asked 2020-Apr-22 at 09:13

Similar questions were posted here and here, and my question is actually based on what was suggested in answers to those questions.

I try to parse some German texts using Stanford Parser and NLTK.

...

ANSWER

Answered 2020-Apr-22 at 09:13

In python \b inside a String is resolved to a backspace character. Therefore you see the white BS in the picture, becuase the console tries to represent this special character (BS for backspace).
What you need to do is to escape the \ inside your String like so

Source https://stackoverflow.com/questions/61360645

QUESTION

Customized StanfordNER

Asked 2020-Jan-21 at 01:09

I am trying to build a customized StanfordNer model, training data and properties file are ready.
But when I am trying to run the following code :

...

ANSWER

Answered 2020-Jan-21 at 01:09

If you are seeing errors like that it means your CLASSPATH is not properly configured.

You need to run that command in the same folder as the NER download or it won't find the needed jars. That command should be run in whatever directory has stanford-ner.jar and lib in it. Alternatively you can just set the CLASSPATH environment variable and remove the -cp option from the command.

More info on Java CLASSPATH here: https://docs.oracle.com/javase/tutorial/essential/environment/paths.html

Source https://stackoverflow.com/questions/59681871

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install stanford-ner

This library spawns a Java process so your system needs to have Java.
Edit tsconfig.js to target es6 instead of es5. Open the folder in VSCode and create a file called index.ts. Then compile by running tsc.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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