Tesnière introduced the dependency trees, structural order, the concept of dependency and applied his representation concepts in a variety of languages such as French, Greek, Russian, Italian, and so on. In structural order, syntactic relations are presented in a hierarchical manner as opposed to the linear order. He uses “stemmas” to reflect hierarchy.
Today, dependency grammars are divided into two. One study from the tradition that applies this distinction to the dependency grammar is the Prague Dependency Treebank (PDT) developed by the Prague School of Functional and Structural Linguistics. A famous example for the other school of thought that displays linear order is the Penn Treebank that functioned between the years of 1989-1996, containing seven million annotated texts from American English.
In 2005, The Stanford Dependencies developed for the parsing of the English language and to be used in NLP studies and in Stanford Dependency Parser. Stanford Dependencies were acknowledged as the standard for the dependency analyses of English. However, the Stanford Dependency parser could not reach an adequate accuracy when it was used with other dependency schemes. In the following years, the Universal Dependency Treebank (UDT) project pioneered to develop treebanks for languages other than English by transforming the Stanford dependencies into a more inclusive annotation scheme for a diverse set of languages.
The developments in the dependency treebanking made it clear that Turkish language needed a Treebank of its own. The first Turkish language dependency treebank is METU-Sabanci Turkish Treebank. This treebank used a corpus that consisted of 7,262 sentences and included morphological and syntactic annotations. In 2016, this tree-bank was revisited under the name of ITU-METU-Sabancı Treebank (IMST) to reduce the inconsistencies of its earlier version. They succeeded to reduce inconsistencies by applying a new annotation scheme. As a last step, The Bogazici-ITU-METU-Sabancı Treebank (BIMST) is updated as the same corpus. Having a linguistic team of three people, they created a new annotation scheme for IMST and manually re-annotated the data of 5.635 sentences while introducing new dependency relations that were not present in IMST.
You can also see either Java, Python, Cython, C, Swift, Js, Php, or C# repository.
To check if you have compatible C++ Compiler installed,
- Open CLion IDE
- Preferences >Build,Execution,Deployment > Toolchain
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 TurkishDependencyParser-CPP will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/TurkishDependencyParser-CPP.git
To import projects from Git with version control:
-
Open CLion IDE , select Get From Version Control.
-
In the Import window, click URL tab and paste github URL.
-
Click open as Project.
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 Project option from Build menu. After compilation process, user can run TestDependencyParser.cpp .
@INPROCEEDINGS{9259799,
author={A. {Kuzgun} and N. {Cesur} and B. N. {Arıcan} and M. {Özçelik} and B. {Marşan} and N. {Kara} and D. B. {Aslan} and O. T. {Yıldız}},
booktitle={2020 Innovations in Intelligent Systems and Applications Conference (ASYU)},
title={On Building the Largest and Cross-Linguistic Turkish Dependency Corpus},
year={2020},
volume={},
number={},
pages={1-6},
doi={10.1109/ASYU50717.2020.9259799}}
- First install conan.
pip install conan
Instructions are given in the following page:
- Add conan remote 'ozyegin' with IP: 104.247.163.162 with the following command:
conan remote add ozyegin http://104.247.163.162:8081/artifactory/api/conan/conan-local --insert
- Use the comman conan list to check for installed packages. Probably there are no installed packages.
conan list
- Put the correct dependencies in the requires part
requires = ["math/1.0.0", "classification/1.0.0"]
- Default settings are:
settings = "os", "compiler", "build_type", "arch"
options = {"shared": [True, False], "fPIC": [True, False]}
default_options = {"shared": True, "fPIC": True}
exports_sources = "src/*", "Test/*"
def layout(self):
cmake_layout(self, src_folder="src")
def generate(self):
tc = CMakeToolchain(self)
tc.generate()
deps = CMakeDeps(self)
deps.generate()
def build(self):
cmake = CMake(self)
cmake.configure()
cmake.build()
def package(self):
copy(conanfile=self, keep_path=False, src=join(self.source_folder), dst=join(self.package_folder, "include"), pattern="*.h")
copy(conanfile=self, keep_path=False, src=self.build_folder, dst=join(self.package_folder, "lib"), pattern="*.a")
copy(conanfile=self, keep_path=False, src=self.build_folder, dst=join(self.package_folder, "lib"), pattern="*.so")
copy(conanfile=self, keep_path=False, src=self.build_folder, dst=join(self.package_folder, "lib"), pattern="*.dylib")
copy(conanfile=self, keep_path=False, src=self.build_folder, dst=join(self.package_folder, "bin"), pattern="*.dll")
def package_info(self):
self.cpp_info.libs = ["ComputationalGraph"]
- Set the C++ standard with compiler flags.
set(CMAKE_CXX_STANDARD 20)
set(CMAKE_CXX_FLAGS "-O3")
- Dependent packages should be given with find_package.
find_package(util_c REQUIRED)
find_package(data_structure_c REQUIRED)
- For library part, use add_library and target_link_libraries commands. Use m library for math linker in Linux.
add_library(Math src/Distribution.cpp src/Distribution.h src/DiscreteDistribution.cpp src/DiscreteDistribution.h src/Vector.cpp src/Vector.h src/Eigenvector.cpp src/Eigenvector.h src/Matrix.cpp src/Matrix.h src/Tensor.cpp src/Tensor.h)
target_link_libraries(Math util_c::util_c data_structure_c::data_structure_c m)
- For executable tests, use add_executable and target_link_libraries commands. Use m library for math linker in Linux.
add_executable(DiscreteDistributionTest src/Distribution.cpp src/Distribution.h src/DiscreteDistribution.cpp src/DiscreteDistribution.h src/Vector.cpp src/Vector.h src/Eigenvector.cpp src/Eigenvector.h src/Matrix.cpp src/Matrix.h src/Tensor.cpp src/Tensor.h Test/DiscreteDistributionTest.cpp)
target_link_libraries(DiscreteDistributionTest util_c::util_c data_structure_c::data_structure_c m)
- Add data files to the cmake-build-debug folder.
- If needed, comparator operators == and < should be implemented for map and set data structures.
bool operator==(const Word &anotherWord) const{
return (name == anotherWord.name);
}
bool operator<(const Word &anotherWord) const{
return (name < anotherWord.name);
}
- Do not forget to comment each function.
/**
* A constructor of Word class which gets a String name as an input and assigns to the name variable.
*
* @param _name String input.
*/
Word::Word(const string &_name) {
- Function names should follow caml case.
int Word::charCount() const
- Write getter and setter methods.
string Word::getName() const
void Word::setName(const string &_name)
- Use catch.hpp for testing purposes. Add
#define CATCH_CONFIG_MAIN // This tells Catch to provide a main() - only do this in one cpp file
line in only one of the test files. Add
#include "catch.hpp"
line in all test files. Example test file is given below:
TEST_CASE("DictionaryTest") {
TxtDictionary lowerCaseDictionary = TxtDictionary("lowercase.txt", "turkish_misspellings.txt");
TxtDictionary mixedCaseDictionary = TxtDictionary("mixedcase.txt", "turkish_misspellings.txt");
TxtDictionary dictionary = TxtDictionary();
SECTION("testSize"){
REQUIRE(29 == lowerCaseDictionary.size());
REQUIRE(58 == mixedCaseDictionary.size());
REQUIRE(62113 == dictionary.size());
}
SECTION("testGetWord"){
for (int i = 0; i < dictionary.size(); i++){
REQUIRE_FALSE(nullptr == dictionary.getWord(i));
}
}
SECTION("testLongestWordSize"){
REQUIRE(1 == lowerCaseDictionary.longestWordSize());
REQUIRE(1 == mixedCaseDictionary.longestWordSize());
REQUIRE(21 == dictionary.longestWordSize());
}
- Enumerated types should be declared with enum class.
enum class Pos {
ADJECTIVE,
NOUN,
VERB,
ADVERB,
- Every header file should start with
#ifndef MATH_DISTRIBUTION_H
#define MATH_DISTRIBUTION_H
and end with
#endif //MATH_DISTRIBUTION_H
- Do not forget to use const expression for parameters, if they will not be changed in the function.
void Word::setName(const string &_name);
- Do not forget to use const expression for methods, which do not modify any class attribute. Also use [[dodiscard]]
[[nodiscard]] bool isPunctuation() const;
- Use xmlparser package for parsing xml files.
auto* doc = new XmlDocument("test.xml");
doc->parse();
XmlElement* root = doc->getFirstChild();
XmlElement* firstChild = root->getFirstChild();
- Data structures: Use map for hash map, unordered_map for linked hash map, vector for array list, unordered_set for hash set