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  • Project: Language Resources and Technologies for Slovene
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  • Service for querying dependency treebanks Drevesnik 1.1

    Drevesnik (https://orodja.cjvt.si/drevesnik/) is an online service for querying Slovenian corpora parsed with the Universal Dependencies annotation scheme. It features an easy-to-use query language on the one hand and user-friendly graph visualizations on the other. It is based on the open-source dep_search tool (https://github.com/TurkuNLP/dep_search), which was localized and modified so as to also support querying by JOS morphosyntactic tags, random distribution of results, and filtering by sentence length. The source code and the documentation for the search backend and the web user interface are publicly available on the CLARIN.SI GitHub repository https://github.com/clarinsi/drevesnik. This submission corresponds to release 1.1: https://github.com/clarinsi/drevesnik/releases/tag/1.1, which brings improved architecture, documentation and branding in comparison to release 1.0.

  • Dependency tree extraction tool STARK 2.0

    STARK is a python-based command-line tool for extraction of dependency trees from parsed corpora, aimed at corpus-driven linguistic investigations of syntactic and lexical phenomena of various kinds. It takes a treebank in the CONLL-U format as input and returns a list of all relevant dependency trees with frequency information and other useful statistics, such as the strength of association between the nodes of a tree, or its significance in comparison to another treebank. For installation, execution and the description of various user-defined parameter settings, see the official project page at: https://github.com/clarinsi/STARK In comparison with v1, this version introduces several new features and improvements, such as the option to set parameters in the command line, compare treebanks or visualise results online.

  • The Trankit model for linguistic processing of standard Slovenian

    This is a retrained Slovenian standard model for Trankit v1.1.1 library (https://pypi.org/project/trankit/). It is able to predict sentence segmentation, tokenization, lemmatization, language-specific morphological annotation (MULTEXT-East morphosyntactic tags), as well as universal part-of-speech tagging, feature prediction, and dependency parsing in accordance with the Universal Dependencies annotation scheme (https://universaldependencies.org/). The model was trained using a dataset published by Universal Dependencies in release 2.12 (https://github.com/UniversalDependencies/UD_Slovenian-SSJ/tree/r2.12). Due to the larger training dataset compared to the original Trankit v1.1.1 model, this version yields superior results and achieves state-of-the art parsing performance for Slovenian (https://slobench.cjvt.si/leaderboard/view/11). To utilize this model, please follow the instructions provided in our github repository (https://github.com/clarinsi/trankit-train) or refer to the Trankit documentation (https://trankit.readthedocs.io/en/latest/training.html#loading). This ZIP file contains models for both xlm-roberta-large (which delivers better performance but requires more hardware resources) and xlm-roberta-base.

  • The Trankit model for linguistic process of standard written Slovenian 1.1

    This is a retrained Slovenian model for the Trankit v1.1.1 library for multilingual natural language processing (https://pypi.org/project/trankit/), trained on the reference SSJ UD treebank featuring fiction, non-fiction, periodical and Wikipedia texts in standard modern Slovenian. It is able to predict sentence segmentation, tokenization, lemmatization, language-specific morphological annotation (MULTEXT-East morphosyntactic tags), as well as universal part-of-speech tagging, morphological features, and dependency parses in accordance with the Universal Dependencies annotation scheme (https://universaldependencies.org/). The model was trained using a dataset published by Universal Dependencies in release 2.14 (https://github.com/UniversalDependencies/UD_Slovenian-SSJ/tree/r2.14). To utilize this model, please follow the instructions provided in our github repository (https://github.com/clarinsi/trankit-train) or refer to the Trankit documentation (https://trankit.readthedocs.io/en/latest/training.html#loading). This ZIP file contains models for both xlm-roberta-large (which delivers better performance but requires more hardware resources) and xlm-roberta-base. This version was trained on a newer, slightly improved version of the SSJ UD treebank (UD v2.14) than the previous version of the model and produces similar results.

  • Corpus extraction tool LIST 1.3

    The LIST corpus extraction tool is a Java program for extracting lists from text corpora on the levels of characters, word parts, words, and word sets. It supports VERT and TEI P5 XML formats and outputs .CSV files that can be imported into Microsoft Excel or similar statistical processing software. Version 1.3 adds support for the KOST 2.0 Slovene Learner Corpus (http://hdl.handle.net/11356/1887) in XML format. It also allows program execution using the command line (see 00README.txt for details), and uses a later version of Java (tested using JDK 21). In addition, Windows users no longer need to have Java installed on their computers to run the program.

  • Q-CAT Corpus Annotation Tool 1.1

    The Q-CAT (Querying-Supported Corpus Annotation Tool) is a computational tool for manual annotation of language corpora, which also enables advanced queries on top of these annotations. The tool has been used in various annotation campaigns related to the ssj500k reference training corpus of Slovenian (http://hdl.handle.net/11356/1210), such as named entities, dependency syntax, semantic roles and multi-word expressions, but it can also be used for adding new annotation layers of various types to this or other language corpora. Q-CAT is a .NET application, which runs on Windows operating system. Version 1.1 enables the automatic attribution of token IDs and personalized font adjustments.

  • Text classification model fastText-Trendi-Topics 1.0

    The fastText-Trendi-Topics model is a text classification model for categorizing news texts with one of 13 topic labels. It was trained on a set of approx. 36,000 Slovene texts from various Slovene news sources included in the Trendi Monitor Corpus of Slovene (http://hdl.handle.net/11356/1590) such as "rtvslo.si", "sta.si", "delo.si", "dnevnik.si", "vecer.com", "24ur.com", "siol.net", "gorenjskiglas.si", etc. The texts were semi-automatically categorized into 13 categories based on the sections under which they were published (i.e. URLs). The set of labels was developed in accordance with related categorization schemas used in other corpora and comprises the following topics: "črna kronika" (crime and accidents), "gospodarstvo, posel, finance" (economy, business, finance), "izobraževanje" (education), "okolje" (environment), "prosti čas" (free time), "šport" (sport), "umetnost, kultura" (art, culture), "vreme" (weather), "zabava" (entertainment), "zdravje" (health), "znanost in tehnologija" (science and technology), "politika" (politics), and "družba" (society). The categorization process is explained in more detail in Kosem et al. (2022): https://nl.ijs.si/jtdh22/pdf/JTDH2022_Kosem-et-al_Spremljevalni-korpus-Trendi.pdf The model was trained on the labeled texts using the word embeddings CLARIN.SI-embed.sl 1.0 (http://hdl.handle.net/11356/1204) and validated on a development set of 1,293 texts using the fastText library, 1000 epochs, and default values for the rest of the hyperparameters (see https://github.com/TajaKuzman/FastText-Classification-SLED for the full code). The model achieves a macro-F1-score of 0.85 on a test set of 1,295 texts (best for "vreme" at 0.97, worst for "prosti čas" at 0.67). Please note that the SloBERTa-Trendi-Topics 1.0 text classification model is also available (http://hdl.handle.net/11356/1709) that achieves higher classification accuracy, but is slower and computationally more demanding.

  • Q-CAT Corpus Annotation Tool 1.3

    The Q-CAT (Querying-Supported Corpus Annotation Tool) is a computational tool for manual annotation of language corpora, which also enables advanced queries on top of these annotations. The tool has been used in various annotation campaigns related to the ssj500k reference training corpus of Slovenian (http://hdl.handle.net/11356/1210), such as named entities, dependency syntax, semantic roles and multi-word expressions, but it can also be used for adding new annotation layers of various types to this or other language corpora. Q-CAT is a .NET application, which runs on Windows operating system. Version 1.1 enables the automatic attribution of token IDs and personalized font adjustments. Version 1.2 supports the CONLL-U format and working with UD POS tags. Version 1.3 supports adding new layers of annotation on top of CONLL-U (and then saving the corpus as XML TEI).

  • Dependency tree extraction tool STARK 3.0

    STARK is a highly customizable tool designed for extracting different types of syntactic structures (trees) from parsed corpora (treebanks), aimed at corpus-driven linguistic investigations of syntactic and lexical phenomena of various kinds. It takes a treebank in the CONLL-U format as input and returns a list of all relevant dependency trees with frequency information and other useful statistics, such as the strength of association between the nodes of a tree, or its significance in comparison to another treebank. For installation, execution and the description of various user-defined parameter settings, see the official project page at: https://github.com/clarinsi/STARK. An online demo version of the tool is available at: https://orodja.cjvt.si/stark/. In comparison to v2, this version introduces several new features and improvements, such as the ability to extract very long trees, ignore irrelevant relations, process multi-root treebanks, or handle special operators when querying.