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.
|LOCATION||regions, mountains, seas|
After annotating sentences, you can use DataGenerator package to generate classification dataset for the Named Entity Recognition task.
After generating the classification dataset as above, one can use the Classification package to generate machine learning models for the Named Entity Recognition task.
Install the latest version of Git.
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 NER-Swift will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/NER-Swift.git
To import projects from Git with version control:
XCode IDE, select Clone an Existing Project.
In the Import window, paste github URL.
Result: The imported project is listed in the Project Explorer view and files are loaded.
After being done with the downloading and opening project, select Build option from Product menu. After compilation process, user can run NER-Swift.