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Constituency TreeBanks

When one talks about the “success” of a Natural Language Processing solution, they often refer to its ability to analyse the semantic and syntactic structure of a given sentence. Such a solution is expected to be able to understand both the linear and hierarchical order of the words in a sentence, unveil embedded structures, illustrate syntactical relationships and have a firm grasp of the argument structure. In order to meet the expectations, cutting edge Natural Language Processing systems like parsers, POS taggers or machine translation systems make use of syntactically or semantically annotated treebanks. Such treebanks offer a deep look through the surface and into the logical form of sentences.

Annotated treebanks can be categorised as constituency treebanks and dependency treebanks. Constituency treebanks offers clarity through resolving structural ambiguities, and successfully illustrates the syntagmatic relations like adjunct, complement, predicate, internal argument, external argument and such.

The very first comprehensive annotated treebank, the Penn Treebank, was created for the English language and offers 40,000 annotated sentences. Following the Penn Treebank, numerous treebanks annotated for constituency structures were developed in different languages including French, German, Finnish, Hungarian, Chinese and Arabic.

TreeBank DataSets

Penn-Treebank 15 Words

Penn-Treebank 20 Words

Video Lectures

For Developers

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

Requirements

Node.js

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

node -v

You can find the latest version of Node.js here.

Git

Install the latest version of Git.

Npm Install

npm install nlptoolkit-parsetree

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

git clone https://github.com/starlangsoftware/parsetree-js.git

Open project with Webstorm IDE

Steps for opening the cloned project:

  • Start IDE
  • Select File | Open from main menu
  • Choose PrseTree-Js file
  • Select open as project option
  • Couple of seconds, dependencies will be downloaded.

Detailed Description

TreeBank

To load a TreeBank composed of saved ParseTrees from a folder:

TreeBank(folder: string)

To load trees with a specified pattern from a folder of trees:

TreeBank(folder: string, pattern: string)

the line above is used. For example,

a = TreeBank("/mypath");

the line below is used to load trees under the folder "mypath" which is under the current folder. If only the trees with ".train" extension under the same folder are to be loaded:

a = TreeBank("/mypath", ".train");

the line below is used.

To iterate over the trees after the TreeBank is loaded:

for (let i = 0; i < a.size(); i++){
	  let p = a.get(i);
}

a block of code like this can be useful.

ParseTree

To load a saved ParseTree:

ParseTree(file: string)

is used. Usually it is more useful to load a TreeBank as explained above than loading the ParseTree one by one.

To find the node number of a ParseTree:

nodeCount(): number

leaf number of a ParseTree:

leafCount(): number

number of words in a ParseTree:

wordCount(excludeStopWords: boolean): number

above methods can be used.

Cite

@INPROCEEDINGS{9259873,
author={N. {Kara} and B. {Marşan} and M. {Özçelik} and B. N. {Arıcan} and A. {Kuzgun} and N. {Cesur} and D. B. {Aslan} and O. T. {Yıldız}},
booktitle={2020 Innovations in Intelligent Systems and Applications Conference (ASYU)}, 
title={Creating A Syntactically Felicitous Constituency Treebank For Turkish}, 
year={2020},
volume={},
number={},
pages={1-6},
doi={10.1109/ASYU50717.2020.9259873}}

For Contibutors

package.json file

  1. main and types are important when this package will be imported.
  "main": "dist/index.js",
  "types": "dist/index.d.ts",
  1. Dependencies should be maximum (not only direct but also indirect references should also be given), everything directly in the code should be given here.
  "dependencies": {
    "nlptoolkit-corpus": "^1.0.12",
    "nlptoolkit-dictionary": "^1.0.14",
    "nlptoolkit-morphologicalanalysis": "^1.0.19",
    "nlptoolkit-xmlparser": "^1.0.7"
  }

tsconfig.json file

  1. Compiler flags currently includes nodeNext for importing.
  "compilerOptions": {
    "outDir": "dist",
    "module": "nodeNext",
    "sourceMap": true,
    "noImplicitAny": true,
    "removeComments": false,
    "declaration": true,
  },
  1. tests, node_modules and dist should be excluded.
  "exclude": [
    "tests",
    "node_modules",
    "dist"
  ]

index.ts file

  1. Should include all ts classes.
export * from "./CategoryType"
export * from "./InterlingualDependencyType"
export * from "./InterlingualRelation"
export * from "./Literal"

Data files

  1. Add data files to the project folder. Subprojects should include all data files of the parent projects.

Javascript files

  1. Classes should be defined as exported.
export class JCN extends ICSimilarity{
  1. Do not forget to comment each function.
    /**
     * Computes JCN wordnet similarity metric between two synsets.
     * @param synSet1 First synset
     * @param synSet2 Second synset
     * @return JCN wordnet similarity metric between two synsets
     */
    computeSimilarity(synSet1: SynSet, synSet2: SynSet): number {
  1. Function names should follow caml case.
    setSynSetId(synSetId: string){
  1. Write getter and setter methods.
    getRelation(index: number): Relation{
    setName(name: string){
  1. Use standard javascript test style.
describe('SimilarityPathTest', function() {
    describe('SimilarityPathTest', function() {
        it('testComputeSimilarity', function() {
            let turkish = new WordNet();
            let similarityPath = new SimilarityPath(turkish);
            assert.strictEqual(32.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0656390"), turkish.getSynSetWithId("TUR10-0600460")));
            assert.strictEqual(13.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0412120"), turkish.getSynSetWithId("TUR10-0755370")));
            assert.strictEqual(13.0, similarityPath.computeSimilarity(turkish.getSynSetWithId("TUR10-0195110"), turkish.getSynSetWithId("TUR10-0822980")));
        });
    });
});
  1. Enumerated types should be declared with enum.
export enum CategoryType {
    MATHEMATICS, SPORT, MUSIC, SLANG, BOTANIC,
    PLURAL, MARINE, HISTORY, THEOLOGY, ZOOLOGY,
    METAPHOR, PSYCHOLOGY, ASTRONOMY, GEOGRAPHY, GRAMMAR,
    MILITARY, PHYSICS, PHILOSOPHY, MEDICAL, THEATER,
    ECONOMY, LAW, ANATOMY, GEOMETRY, BUSINESS,
    PEDAGOGY, TECHNOLOGY, LOGIC, LITERATURE, CINEMA,
    TELEVISION, ARCHITECTURE, TECHNICAL, SOCIOLOGY, BIOLOGY,
    CHEMISTRY, GEOLOGY, INFORMATICS, PHYSIOLOGY, METEOROLOGY,
    MINERALOGY
}
  1. If there are multiple constructors for a class, define them as constructor1, constructor2, ..., then from the original constructor call these methods.
    constructor1(symbol: any){
    constructor2(symbol: any, multipleFile: MultipleFile) {
    constructor(symbol: any, multipleFile: MultipleFile = undefined) {
        if (multipleFile == undefined){
            this.constructor1(symbol);
        } else {
            this.constructor2(symbol, multipleFile);
        }
    }
  1. Importing should be done via import method with referencing the node-modules.
import {Corpus} from "nlptoolkit-corpus/dist/Corpus";
import {Sentence} from "nlptoolkit-corpus/dist/Sentence";
  1. Use xmlparser package for parsing xml files.
	var doc = new XmlDocument("test.xml")
	doc.parse()
	let root = doc.getFirstChild()
	let firstChild = root.getFirstChild()

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Constituency Parse Tree Library

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