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StarlangSoftware/AnnotatedSentence-Swift 1.0.9
Annotated Sentence Processing Library
⭐️ 0
🕓 1 year ago
.package(url: "https://github.com/StarlangSoftware/AnnotatedSentence-Swift.git", from: "1.0.9")

This resource allows for matching of Turkish words or expressions with their corresponding entries within the Turkish dictionary, the Turkish PropBank TRopBank, morphological analysis, named entity recognition, word senses from Turkish WordNet KeNet, shallow parsing, and universal dependency relation.

Data Format

The structure of a sample annotated word is as follows:


As is self-explanatory, 'turkish' tag shows the original Turkish word; 'morphologicalAnalysis' tag shows the correct morphological parse of that word; 'semantics' tag shows the ID of the correct sense of that word; 'namedEntity' tag shows the named entity tag of that word; 'shallowParse' tag shows the semantic role of that word; 'universalDependency' tag shows the index of the head word and the universal dependency for this word; 'propbank' tag shows the semantic role of that word for the verb synset id (frame id in the frame file) which is also given in that tag.

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For Developers

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


  • Xcode Editor
  • 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 AnnotatedSentence-Swift will be created. Or you can use below link for exploring the code:

git clone https://github.com/starlangsoftware/AnnotatedSentence-Swift.git

Open project with XCode

To import projects from Git with version control:

  • XCode IDE, select Clone an Existing Project.

  • In the Import window, paste github URL.

  • Click Clone.

Result: The imported project is listed in the Project Explorer view and files are loaded.


From IDE

After being done with the downloading and opening project, select Build option from Product menu. After compilation process, user can run AnnotatedSentence-Swift.

Detailed Description


To load the annotated corpus:

AnnotatedCorpus(folder: String, pattern: String)
let a = AnnotatedCorpus("/Turkish-Phrase", ".train")
let b = AnnotatedCorpus("/Turkish-Phrase")

To access all the sentences in a AnnotatedCorpus:

for i in 0..<a.sentenceCount(){
	let annotatedSentence = a.getSentence(i)


Bir AnnotatedSentence'daki tüm kelimelere ulaşmak için de

for j in 0..<annotatedSentence.wordCount(){
	annotatedWord = annotatedSentence.getWord(j)


An annotated word is kept in AnnotatedWord class. To access the morphological analysis of the annotated word:

getParse() -> MorphologicalParse

Meaning of the annotated word:

getSemantic() -> String

NER annotation of the annotated word:

getNamedEntityType() -> NamedEntityType

Shallow parse tag of the annotated word (e.g., subject, indirect object):

getShallowParse() -> String

Dependency annotation of the annotated word:

getUniversalDependency() -> UniversalDependencyRelation


author={O. T. {Yıldız} and K. {Ak} and G. {Ercan} and O. {Topsakal} and C. {Asmazoğlu}},
booktitle={2018 2nd International Conference on Natural Language and Speech Processing (ICNLSP)}, 
title={A multilayer annotated corpus for Turkish}, 

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