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Named Entity Recognition Task

In named entity recognition, one tries to find the strings within a text that correspond to proper names (excluding TIME and MONEY) and classify the type of entity denoted by these strings. The problem is difficult partly due to the ambiguity in sentence segmentation; one needs to extract which words belong to a named entity, and which not. Another difficulty occurs when some word may be used as a name of either a person, an organization or a location. For example, Deniz may be used as the name of a person, or - within a compound - it can refer to a location Marmara Denizi 'Marmara Sea', or an organization Deniz Taşımacılık 'Deniz Transportation'.

The standard approach for NER is a word-by-word classification, where the classifier is trained to label the words in the text with tags that indicate the presence of particular kinds of named entities. After giving the class labels (named entity tags) to our training data, the next step is to select a group of features to discriminate different named entities for each input word.

[ORG Türk Hava Yolları] bu [TIME Pazartesi'den] itibaren [LOC İstanbul] [LOC Ankara] hattı için indirimli satışlarını [MONEY 90 TL'den] başlatacağını açıkladı.

[ORG Turkish Airlines] announced that from this [TIME Monday] on it will start its discounted fares of [MONEY 90TL] for [LOC İstanbul] [LOC Ankara] route.

See the Table below for typical generic named entity types.

Tag Sample Categories
PERSON people, characters
ORGANIZATION companies, teams
LOCATION regions, mountains, seas
TIME time expressions
MONEY monetarial expressions

Video Lectures

Class Diagram

For Developers

You can also see Python, Cython, C, C++, Swift, Js, or C# repository.

Requirements

Java

To check if you have a compatible version of Java installed, use the following command:

java -version

If you don't have a compatible version, you can download either Oracle JDK or OpenJDK

Maven

To check if you have Maven installed, use the following command:

mvn --version

To install Maven, you can follow the instructions here.

Git

Install the latest version of Git.

Download Code

In order to work on code, create a fork from GitHub page. Use Git for cloning the code to your local or below line for Ubuntu:

git clone <your-fork-git-link>

A directory called NamedEntityRecognition will be created. Or you can use below link for exploring the code:

git clone https://github.com/starlangsoftware/TurkishNamedEntityRecognition.git

Open project with IntelliJ IDEA

Steps for opening the cloned project:

  • Start IDE
  • Select File | Open from main menu
  • Choose NamedEntityRecognition/pom.xml file
  • Select open as project option
  • Couple of seconds, dependencies with Maven will be downloaded.

Compile

From IDE

After being done with the downloading and Maven indexing, select Build Project option from Build menu. After compilation process, user can run NamedEntityRecognition.

From Console

Go to NamedEntityRecognition directory and compile with

 mvn compile

Generating jar files

From IDE

Use package of 'Lifecycle' from maven window on the right and from NamedEntityRecognition root module.

From Console

Use below line to generate jar file:

 mvn install

Maven Usage

    <dependency>
        <groupId>io.github.starlangsoftware</groupId>
        <artifactId>NamedEntityRecognition</artifactId>
        <version>1.0.11</version>
    </dependency>

Detailed Description

Gazetteer

Bir Gazetter yüklemek için

Gazetteer(String name, String fileName)

Hazır Gazetteerleri kullanmak için

AutoNER()

Bir Gazetteer'de bir kelime var mı diye kontrol etmek için

boolean contains(String word)

Cite

@INPROCEEDINGS{8093439,
author={B. {Ertopçu} and A. B. {Kanburoğlu} and O. {Topsakal} and O. {Açıkgöz} and A. T. {Gürkan} and B. {Özenç} and İ. {Çam} and B. {Avar} and G. {Ercan} 	and O. T. {Yıldız}},
booktitle={2017 International Conference on Computer Science and Engineering (UBMK)}, 
title={A new approach for named entity recognition}, 
year={2017},
volume={},
number={},
pages={474-479},
doi={10.1109/UBMK.2017.8093439}}