Text-Processing

FREEMIUM
By japerk
Updated 5 months ago
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jdimm5 years ago
Obama is an ORG?Input to NER tagger: Barack Obama and Clinton Output: { "text": "(S\n (PERSON Barack/NNP)\n (ORGANIZATION Obama/NNP)\n and/CC\n (PERSON Clinton/NNP))" } I'll try some more, but this is a pretty easy test case. You must have seen "Barack Obama" frequently in training data.
jdimm5 years ago
Another test: Barack Obama and Hilary Clinton and Mitt Romney and Michele Obama and Barack Obama That gets all but the first "Obama". The "Barack Obama" at the end of the string is correctly identified.
japerk5 years ago
NER tends to work better in a real context instead of just lists of names. But my models are also trained on somewhat old data, so I'm not sure they've actually encountered Obama specifically.
Hi Developer, feel free to post your answer:

Install SDK for NodeJS

Installing

To utilize unirest for node.js install the the npm module:

$ npm install unirest

After installing the npm package you can now start simplifying requests like so:

var unirest = require('unirest');

Creating Request

unirest.post("https://japerk-text-processing.p.rapidapi.com/phrases/")
.header("X-RapidAPI-Host", "japerk-text-processing.p.rapidapi.com")
.header("X-RapidAPI-Key", "SIGN-UP-FOR-KEY")
.header("Content-Type", "application/x-www-form-urlencoded")
.send("language=spanish")
.send("text=California is nice")
.end(function (result) {
  console.log(result.status, result.headers, result.body);
});
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