nlptoolkit-annotatedtree-cy 1.0.16
Annotated constituency treebank library

# Constituency TreeBank

A treebank is a corpus where the sentences in each language are syntactically (if necessary morphologically) annotated. In the treebanks, the syntactic annotation usually follows constituent and/or dependency structure.

Treebanks annotated for the syntactic or semantic structures of the sentences are essential for developing state-of-the-art statistical natural language processing (NLP) systems including part-of-speech-taggers, syntactic parsers, and machine translation systems. There are two main groups of syntactic treebanks, namely treebanks annotated for constituency (phrase structure) and the ones that are annotated for dependency structure.

## Data Format

We extend the original format with the relevant information, given between curly braces. For example, the word 'problem' in a sentence in the standard Penn Treebank notation, may be represented in the data format provided below:

	(NN problem)

After all levels of processing are finished, the data structure stored for the same word has the following form in the system.

	(NN {turkish=sorunu} {english=problem} 
	{morphologicalAnalysis=sorun+NOUN+A3SG+PNON+ACC}
	{metaMorphemes=sorun+yH}
	{semantics=TUR10-0703650})

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; '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.

Video Lectures
============

[<img src=https://github.com/StarlangSoftware/AnnotatedTree/blob/master/video1.jpg width="50%">](https://youtu.be/LfMf1bo3tEw)[<img src=https://github.com/StarlangSoftware/AnnotatedTree/blob/master/video2.jpg width="50%">](https://youtu.be/QoFPb9XY8Vc)

For Developers
============
You can also see [Python](https://github.com/starlangsoftware/AnnotatedTree-Py), [Java](https://github.com/starlangsoftware/AnnotatedTree), [C++](https://github.com/starlangsoftware/AnnotatedTree-CPP), [C](https://github.com/starlangsoftware/AnnotatedTree-C), [Js](https://github.com/starlangsoftware/AnnotatedTree-Js), [Swift](https://github.com/starlangsoftware/AnnotatedTree-Swift), or [C#](https://github.com/starlangsoftware/AnnotatedTree-CS) repository.

## Requirements

* [Python 3.7 or higher](#python)
* [Maven](#maven)
* [Git](#git)

### Python 

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

    python -V
    
You can find the latest version of Python [here](https://www.python.org/downloads/).

### Git

Install the [latest version of Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).

## Pip Install

	pip3 install NlpToolkit-AnnotatedTree-Cy

## 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 DataStructure will be created. Or you can use below link for exploring the code:

	git clone https://github.com/starlangsoftware/AnnotatedTree-Cy.git

## Open project with Pycharm IDE

Steps for opening the cloned project:

* Start IDE
* Select **File | Open** from main menu
* Choose `AnnotatedTree-Cy` file
* Select open as project option
* Couple of seconds, dependencies will be downloaded. 

Detailed Description
============

+ [TreeBankDrawable](#treebankdrawable)
+ [ParseTreeDrawable](#parsetreedrawable)
+ [LayerInfo](#layerinfo)

## TreeBankDrawable

To load an annotated TreeBank:

	TreeBankDrawable(folder: str, String pattern: str)
	a = TreeBankDrawable("/Turkish-Phrase", ".train")

	TreeBankDrawable(folder: str)
	a = new TreeBankDrawable("/Turkish-Phrase")

To access all the trees in a TreeBankDrawable:

	for i in range(a.sentenceCount()):
		parseTree = a.get(i);
		....
	}

## ParseTreeDrawable

To load a saved ParseTreeDrawable:

	ParseTreeDrawable(file: str)
	
is used. Usually it is more useful to load TreeBankDrawable as explained above than to load ParseTree one by one.

To find the node number of a ParseTreeDrawable:

	nodeCount() -> int
	
the leaf number of a ParseTreeDrawable:

	leafCount() -> int
	
the word count in a ParseTreeDrawable:

	wordCount(excludeStopWords: bool) -> int
	
above methods can be used.

## LayerInfo

Information of an annotated word is kept in LayerInfo class. To access the morphological analysis
of the annotated word:

	getMorphologicalParseAt(index: int) -> MorphologicalParse

meaning of an annotated word:

	getSemanticAt(self, index: int) -> str

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

	getShallowParseAt(self, index: int) -> str

the argument tag of the annotated word:

	getArgumentAt(self, index: int) -> Argument
	
the word count in a node:

	getNumberOfWords(self) -> int

# Cite

	@inproceedings{yildiz-etal-2014-constructing,
    	title = "Constructing a {T}urkish-{E}nglish Parallel {T}ree{B}ank",
    	author = {Y{\i}ld{\i}z, Olcay Taner  and
      	Solak, Ercan  and
      	G{\"o}rg{\"u}n, Onur  and
      	Ehsani, Razieh},
    	booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
    	month = jun,
    	year = "2014",
    	address = "Baltimore, Maryland",
    	publisher = "Association for Computational Linguistics",
    	url = "https://www.aclweb.org/anthology/P14-2019",
    	doi = "10.3115/v1/P14-2019",
    	pages = "112--117",
	}