Named Entity Recognition

No algorithm description given

The Name Finder can detect named entities and numbers in text. It is currently set to detect persons (proper names), organizations, locations, times, dates, money, and percentages. To be able to detect entities the Name Finder needs a model. The model is dependent on the language and entity type it was trained for. The OpenNLP projects offers a number of pre-trained name finder models which are trained on various freely available corpora. They are available in data://ApacheOpenNLP/models/. To find names in raw text the text must be segmented into tokens and sentences, which this implementation handles by default for standard English. Its important that the tokenization for the training data and the input text is identical, so if working with something other than standard English, you need to pick different models from the models directory or train your own. For more information visit http://opennlp.apache.org .

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This algorithm has permission to call other algorithms. This allows an algorithm to compose sophisticated functionality using other algorithms as building blocks, however it also carries the potential of incurring additional royalty and usage costs from any algorithm that it calls.


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1. Type your input

2. See the result

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3. Use this algorithm

curl -X POST -d '{{input | formatInput:"curl"}}' -H 'Content-Type: application/json' -H 'Authorization: Simple YOUR_API_KEY' https://api.algorithmia.com/v1/algo/ApacheOpenNLP/NamedEntityRecognition/0.1.1
View cURL Docs
algo auth
# Enter API Key: YOUR_API_KEY
algo run algo://ApacheOpenNLP/NamedEntityRecognition/0.1.1 -d '{{input | formatInput:"cli"}}'
View CLI Docs
import com.algorithmia.*;
import com.algorithmia.algo.*;

String input = "{{input | formatInput:"java"}}";
AlgorithmiaClient client = Algorithmia.client("YOUR_API_KEY");
Algorithm algo = client.algo("algo://ApacheOpenNLP/NamedEntityRecognition/0.1.1");
AlgoResponse result = algo.pipeJson(input);
System.out.println(result.asJsonString());
View Java Docs
import com.algorithmia._
import com.algorithmia.algo._

val input = {{input | formatInput:"scala"}}
val client = Algorithmia.client("YOUR_API_KEY")
val algo = client.algo("algo://ApacheOpenNLP/NamedEntityRecognition/0.1.1")
val result = algo.pipeJson(input)
System.out.println(result.asJsonString)
View Scala Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://ApacheOpenNLP/NamedEntityRecognition/0.1.1")
           .pipe(input)
           .then(function(output) {
             console.log(output);
           });
View Javascript Docs
var input = {{input | formatInput:"javascript"}};
Algorithmia.client("YOUR_API_KEY")
           .algo("algo://ApacheOpenNLP/NamedEntityRecognition/0.1.1")
           .pipe(input)
           .then(function(response) {
             console.log(response.get());
           });
View NodeJS Docs
import Algorithmia

input = {{input | formatInput:"python"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('ApacheOpenNLP/NamedEntityRecognition/0.1.1')
print algo.pipe(input)
View Python Docs
library(algorithmia)

input <- {{input | formatInput:"r"}}
client <- getAlgorithmiaClient("YOUR_API_KEY")
algo <- client$algo("ApacheOpenNLP/NamedEntityRecognition/0.1.1")
result <- algo$pipe(input)$result
print(result)
View R Docs
require 'algorithmia'

input = {{input | formatInput:"ruby"}}
client = Algorithmia.client('YOUR_API_KEY')
algo = client.algo('ApacheOpenNLP/NamedEntityRecognition/0.1.1')
puts algo.pipe(input).result
View Ruby Docs
use algorithmia::*;

let input = {{input | formatInput:"rust"}};
let client = Algorithmia::client("YOUR_API_KEY");
let algo = client.algo("ApacheOpenNLP/NamedEntityRecognition/0.1.1");
let response = algo.pipe(input);
View Rust Docs
import Algorithmia

let input = "{{input | formatInput:"swift"}}";
let client = Algorithmia.client(simpleKey: "YOUR_API_KEY")
let algo = client.algo(algoUri: "ApacheOpenNLP/NamedEntityRecognition/0.1.1") { resp, error in
  print(resp)
}
View Swift Docs
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