NlpToolkit-Dictionary-Cy 1.0.31

Simple Dictionary Processing

Turkish Dictionary

This resource is a dictionary of Modern Turkish, comprised of the definitions of over 50.000 individual entries. Each entry is matched with its corresponding synset (set of synonymous words and expressions) in the Turkish WordNet, KeNet.

The bare-forms in the lexicon consists of nouns, adjectives, verbs, adverbs, shortcuts, etc. Each bare-form appears the same in the lexicon except verbs. Since the bare-forms of the verbs in Turkish do not have the infinitive affix ‘mAk’, our lexicon includes all verbs without the infinitive affix. The bare-forms with diacritics are included in two forms, with and without diacritics. For example, noun ‘rüzgar’ appear both as ‘rüzgar’ and ‘rüzgâr’.

Special markers are included as bare-forms such as doc, s, etc.

Some compound words are included in their affixed form. For instance, ‘acemlalesi’ appears as it is, but not as ‘acemlale’.

Foreign words, especially proper noun foreign words, are included, so that the system can easily recognize them as proper nouns. For instance, the words ‘abbott’, ‘abbigail’ are example foreign proper nouns. Including foreign proper nouns, there are 19,000 proper nouns in our lexicon.

From derivational suffixes, we only include words which has taken -lI, -sIz, -CI, -lIk, and -CIlIk derivational affixes. For example, the bare-forms ‘abacı’, ‘abdallık’, ‘abdestli’ and ‘abdestlilik’, are included, since they have taken one or more derivational affixes listed above.

Each bare-form has a set of attributes. For instance, ‘abacı’ is a noun, therefore, it includes CL_ISIM attribute. Similarly, ‘abdestli’ is an adjective, which includes IS_ADJ attribute. If the bare-form has homonyms with different part of speech tags, all corresponding attributes are included.

Name	Purpose
CL ISIM, CL FIIL, IS_OA	Part of speech tag(s)
IS_DUP	Part of a duplicate form
IS_KIS	Abbreviation, which does not obey vowel harmony while taking suffixes.
IS_UU, IS_UUU	Does not obey vowel harmony while taking suffixes.
IS_BILES	A portmanteau word in affixed form, such as ‘adamotu’
IS_B_SI	A portmanteau word ending with ‘sı’, such as ‘acemlalesi’
IS_CA	Already in a plural form, therefore can not take plural suffixes such as ‘ler’ or ‘lar’.
IS_ST	The second consonant undergoes a resyllabification.
IS_UD, IS_UDD, F_UD	Includes vowel epenthesis.
IS_KG	Ends with a ‘k’, and when it is followed by a vowel-initial suffix, the final ‘k’ is replaced with a ‘g’.
IS_SD, IS_SDD, F_SD	Final consonant gets devoiced during vowel-initial suffixation.
F GUD, F_GUDO	The verb bare-form includes vowel reduction.
F1P1, F1P1-NO-REF	A verb, and depending on this attribute, the verb can (or can not) take causative suffix, factitive suffix, passive suffix etc.

Video Lectures

For Developers

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

Requirements

• Python 3.7 or higher
• 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.

Git

Install the latest version of Git.

Pip Install

pip3 install NlpToolkit-Dictionary-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 Dictionary will be created. Or you can use below link for exploring the code:

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

Open project with Pycharm IDE

Steps for opening the cloned project:

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

Detailed Description

• TxtDictionary
• TxtWord
• SyllableList

TxtDictionary

Dictionary is used in order to load Turkish dictionary or a domain specific dictionary. In addition, misspelled words and the true forms of the misspelled words can also be loaded.

To load the Turkish dictionary and the misspelled words dictionary,

a = TxtDictionary()

To load the domain specific dictionary and the misspelled words dictionary,

TxtDictionary(self, fileName=None, misspelledFileName=None)

And to see if the dictionary involves a specific word, getWord is used.

getWord(self, name: str) -> Word

TxtWord

The word features: To see whether the TxtWord class of the dictionary is a noun or not,

isNominal(self) -> bool

To see whether it is an adjective,

isAdjective(self) -> bool

To see whether it is a portmanteau word,

isPortmanteau(self) -> bool

To see whether it obeys vowel harmony,

notObeysVowelHarmonyDuringAgglutination(self) -> bool

And, to see whether it softens when it get affixes, the following is used.

rootSoftenDuringSuffixation(self) -> bool

SyllableList

To syllabify the word, SyllableList class is used.

SyllableList(self, word: str)

Cite

@inproceedings{yildiz-etal-2019-open,
	title = "An Open, Extendible, and Fast {T}urkish Morphological Analyzer",
	author = {Y{\i}ld{\i}z, Olcay Taner  and
  	Avar, Beg{\"u}m  and
  	Ercan, G{\"o}khan},
	booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
	month = sep,
	year = "2019",
	address = "Varna, Bulgaria",
	publisher = "INCOMA Ltd.",
	url = "https://www.aclweb.org/anthology/R19-1156",
	doi = "10.26615/978-954-452-056-4_156",
	pages = "1364--1372",
}