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[Utility & Helpers](/categories/utility) 4. / 5. olcaytaner/semanticrolelabeling ActiveLibrary[Utility & Helpers](/categories/utility) olcaytaner/semanticrolelabeling =============================== Semantic Role Labeling Library 1.0.0(6mo ago)00GPL-3.0-or-laterPHP Since Oct 27Pushed 1mo agoCompare [ Source](https://github.com/StarlangSoftware/SemanticRoleLabeling-Php)[ Packagist](https://packagist.org/packages/olcaytaner/semanticrolelabeling)[ RSS](/packages/olcaytaner-semanticrolelabeling/feed)WikiDiscussions main Synced 1mo ago READMEChangelog (1)Dependencies (13)Versions (2)Used By (0) Semantic Role Labeling ====================== [](#semantic-role-labeling) Task Definition --------------- [](#task-definition) Semantic Role Labeling (SRL) is a well-defined task where the objective is to analyze propositions expressed by the verb. In SRL, each word that bears a semantic role in the sentence has to be identified. There are different types of arguments (also called ’thematic roles’) such as Agent, Patient, Instrument, and also of adjuncts, such as Locative, Temporal, Manner, and Cause. These arguments and adjuncts represent entities participating in the event and give information about the event characteristics. In the field of SRL, PropBank is one of the studies widely recognized by the computational linguistics communities. PropBank is the bank of propositions where predicate- argument information of the corpora is annotated, and the semantic roles or arguments that each verb can take are posited. Each verb has a frame file, which contains arguments applicable to that verb. Frame files may include more than one roleset with respect to the senses of the given verb. In the roleset of a verb sense, argument labels Arg0 to Arg5 are described according to the meaning of the verb. For the example below, the predicate is “announce” from PropBank, Arg0 is “announcer”, Arg1 is “entity announced”, and ArgM- TMP is “time attribute”. \[ARG0 Türk Hava Yolları\] \[ARG1 indirimli satışlarını\] \[ARGM-TMP bu Pazartesi\] \[PREDICATE açıkladı\]. \[ARG0 Turkish Airlines\] \[PREDICATE announced\] \[ARG1 its discounted fares\] \[ARGM-TMP this Monday\]. The following Table shows typical semantic role types. Only Arg0 and Arg1 indicate the same thematic roles across different verbs: Arg0 stands for the Agent or Causer and Arg1 is the Patient or Theme. The rest of the thematic roles can vary across different verbs. They can stand for Instrument, Start point, End point, Beneficiary, or Attribute. Moreover, PropBank uses ArgM’s as modifier labels indicating time, location, temporal, goal, cause etc., where the role is not specific to a single verb group; it generalizes over the entire corpus instead. TagMeaningArg0Agent or CauserArgM-EXTExtentArg1Patient or ThemeArgM-LOCLocativesArg2Instrument, start point, end point, beneficiary, or attributeArgM-CAUCauseArgM-MNRMannerArgM-DISDiscourseArgM-ADVAdverbialsArgM-DIRDirectionalsArgM-PNCPurposeArgM-TMPTemporalsData Annotation --------------- [](#data-annotation) ### Preparation [](#preparation) 1. Collect a set of sentences to annotate. 2. Each sentence in the collection must be named as xxxx.yyyyy in increasing order. For example, the first sentence to be annotated will be 0001.train, the second 0002.train, etc. 3. Put the sentences in the same folder such as *Turkish-Phrase*. 4. Build the [Java](https://github.com/starlangsoftware/SemanticRoleLabeling) project and put the generated sentence-propbank-predicate.jar and sentence-propbank-argument.jar files into another folder such as *Program*. 5. Put *Turkish-Phrase* and *Program* folders into a parent folder. ### Predicate Annotation [](#predicate-annotation) 1. Open sentence-propbank-predicate.jar file. 2. Wait until the data load message is displayed. 3. Click Open button in the Project menu. 4. Choose a file for annotation from the folder *Turkish-Phrase*. 5. For each predicate word in the sentence, click the word, and choose PREDICATE tag for that word. 6. Click one of the next buttons to go to other files. ### Argument Annotation [](#argument-annotation) 1. Open sentence-propbank-argument.jar file. 2. Wait until the data load message is displayed. 3. Click Open button in the Project menu. 4. Choose a file for annotation from the folder *Turkish-Phrase*. 5. For each word in the sentence, click the word, and choose correct argument tag for that word. 6. Click one of the next buttons to go to other files. Classification DataSet Generation --------------------------------- [](#classification-dataset-generation) After annotating sentences, you can use [DataGenerator](https://github.com/starlangsoftware/DataGenerator-CS) package to generate classification dataset for the Semantic Role Labeling task. Generation of ML Models ----------------------- [](#generation-of-ml-models) After generating the classification dataset as above, one can use the [Classification](https://github.com/starlangsoftware/Classification-CS) package to generate machine learning models for the Semantic Role Labeling task. Annotated DataSets ================== [](#annotated-datasets) PropBank Annotation ------------------- [](#propbank-annotation) [Atis & Framenet & Tourism](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-propbank1.html) [Kenet](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-propbank2.html) [Penn-Treebank](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-propbank3.html) Framenet Annotation ------------------- [](#framenet-annotation) [Atis & Framenet & Tourism](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-framenet1.html) [Kenet](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-framenet2.html) [Penn-Treebank](http://104.247.163.162/nlptoolkit/turkish-semanticrolelabeling-framenet3.html) For Developers ============== [](#for-developers) You can also see [Java](https://github.com/starlangsoftware/SemanticRoleLabeling), [Python](https://github.com/starlangsoftware/SemanticRoleLabeling-Py), [Cython](https://github.com/starlangsoftware/SemanticRoleLabeling-Cy), [Js](https://github.com/starlangsoftware/SemanticRoleLabeling-Js), [C#](https://github.com/starlangsoftware/SemanticRoleLabeling-CS), [Swift](https://github.com/starlangsoftware/SemanticRoleLabeling-Swift), or [C++](https://github.com/starlangsoftware/SemanticRoleLabeling-CPP) repository. For Contibutors =============== [](#for-contibutors) ### composer.json file [](#composerjson-file) 1. autoload is important when this package will be imported. ``` "autoload": { "psr-4": { "olcaytaner\\WordNet\\": "src/" } }, ``` 2. Dependencies should be maximum (not only direct but also indirect references should also be given), everything directly in the code should be given here. ``` "require-dev": { "phpunit/phpunit": "11.4.0", "olcaytaner/dictionary": "1.0.0", "olcaytaner/xmlparser": "1.0.1", "olcaytaner/morphologicalanalysis": "1.0.0" } ``` ### Data files [](#data-files) 1. Add data files to the project folder. Subprojects should include all data files of the parent projects. ### Php files [](#php-files) 1. Do not forget to comment each function. ``` /** * Returns true if specified semantic relation type presents in the relations list. * * @param SemanticRelationType $relationType element whose presence in the list is to be tested * @return bool true if specified semantic relation type presents in the relations list */ public function containsRelationType(SemanticRelationType $relationType): bool{ foreach ($this->relations as $relation){ if ($relation instanceof SematicRelation && $relation->getRelationType() == $relationType){ return true; } } return false; } ``` 2. Function names should follow caml case. ``` public function getRelation(int $index): Relation{ ``` 3. Write getter and setter methods. ``` public function getOrigin(): ?string public function setName(string $name): void ``` 4. Use standard javascript test style by extending the TestCase class. Use setup when necessary. ``` class WordNetTest extends TestCase { private WordNet $turkish; protected function setUp(): void { ini_set('memory_limit', '450M'); $this->turkish = new WordNet(); } public function testSize() { $this->assertEquals(78327, $this->turkish->size()); } ``` 5. Enumerated types should be declared with enum. ``` enum CategoryType { case MATHEMATICS; case SPORT; case MUSIC; case SLANG; case BOTANIC; ``` 6. If there are multiple constructors for a class, define them as constructor1, constructor2, ..., then from the original constructor call these methods. ``` public function constructor1(string $path, string $fileName): void public function constructor2(string $path, string $extension, int $index): void public function __construct(string $path, string $extension, ?int $index = null) ``` 7. Use \_\_toString method if necessary to create strings from objects. ``` public function __toString(): string ``` 8. Use xmlparser package for parsing xml files. ``` $doc = new XmlDocument("../test.xml"); $doc->parse(); $root = $doc->getFirstChild(); $firstChild = $root->getFirstChild(); ``` ### Health Score 31 — LowBetter than 68% of packages Maintenance79 Regular maintenance activity Popularity0 Limited adoption so far Community6 Small or concentrated contributor base Maturity35 Early-stage or recently created project Bus Factor1 Top contributor holds 100% of commits — single point of failure How is this calculated?**Maintenance (25%)** — Last commit recency, latest release date, and issue-to-star ratio. Uses a 2-year decay window. **Popularity (30%)** — Total and monthly downloads, GitHub stars, and forks. Logarithmic scaling prevents top-heavy scores. **Community (15%)** — Contributors, dependents, forks, watchers, and maintainers. Measures real ecosystem engagement. **Maturity (30%)** — Project age, version count, PHP version support, and release stability. ### Release Activity Cadence Unknown Total 1 Last Release 197d ago ### Community Maintainers ![](https://www.gravatar.com/avatar/8903e2f2ee6f2b7849f720cf76786a074796f23ac27e12bde3036de5ca12de3f?d=identicon)[olcaytaner](/maintainers/olcaytaner) --- Top Contributors [![olcaytaner](https://avatars.githubusercontent.com/u/39756553?v=4)](https://github.com/olcaytaner "olcaytaner (3 commits)") ### Code Quality TestsPHPUnit ### Embed Badge ![Health badge](/badges/olcaytaner-semanticrolelabeling/health.svg) ``` [![Health](https://phpackages.com/badges/olcaytaner-semanticrolelabeling/health.svg)](https://phpackages.com/packages/olcaytaner-semanticrolelabeling) ``` ### Alternatives [aneeshikmat/yii2-time-down-counter Widget for yii2, to start count down timer with a lot of options, This widget build dependence of timeDownCounter JS library 1546.0k](/packages/aneeshikmat-yii2-time-down-counter)[optimistdigital/nova-resizable Simple Laravel Nova tool to enable column resizing 1818.9k](/packages/optimistdigital-nova-resizable)[haruncpi/laravel-simple-captcha A laravel simple captcha package 1128.3k](/packages/haruncpi-laravel-simple-captcha) PHPackages © 2026 [Directory](/)[Categories](/categories)[Trending](/trending)[Changelog](/changelog)[Analyze](/analyze)