--- dataset_info: features: - name: id dtype: string - name: tokens sequence: string - name: pos_tags sequence: class_label: names: '0': ADJ '1': ADP '2': ADV '3': AUX '4': CCONJ '5': DET '6': INTJ '7': NOUN '8': NUM '9': PART '10': PRON '11': PROPN '12': PUNCT '13': SCONJ '14': SYM '15': VERB '16': X splits: - name: latin num_bytes: 114634 num_examples: 500 - name: cyrillic num_bytes: 143553 num_examples: 500 download_size: 99179 dataset_size: 258187 configs: - config_name: default data_files: - split: latin path: data/latin-* - split: cyrillic path: data/cyrillic-* license: apache-2.0 task_categories: - token-classification language: - uz tags: - pos - uz - upos pretty_name: uzbekpos size_categories: - n<1K --- # Dataset Card for "uzbekpos" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [Uzbek UD](https://universaldependencies.org/uz/index.html) - **Repository:** [UD_Uzbek-UT (conllu format)](https://github.com/UniversalDependencies/UD_Uzbek-UT) - **Paper:** [BBPOS: BERT-based Part-of-Speech Tagging for Uzbek](https://arxiv.org/abs/2501.10107) - **Point of Contact:** latofatbobojonova@gmail.com or arofat.akhundjanova@gmail.com - **Size of downloaded dataset files:** 99.2 kB ### Dataset Summary Uzbek POS: First UPOS tagged dataset for Part-of-Speech tagging task This dataset is an annotated dataset for POS tagging. It contains 250 sample sentences collected from news outlets and fictional books respectively. The dataset is presented in both Uzbek scripts i.e., Latin and Cyrillic. The annotation was done manually according to [UPOS tagset](https://universaldependencies.org/u/pos/). ### Languages - Northern Uzbek (_a.k.a_ Uzbek) ## Dataset Structure ### Data Instances - **Size of downloaded dataset files:** 99.2 kB - **Size of the generated dataset:** 99.2 kB - **Total amount of disk used:** 99.2 kB An example of 'latin' looks as follows. ``` { 'id': 0, 'tokens': "['Doimiy', 'g‘ala-g‘ovur', ',', 'to‘lib-toshgan', 'peshtaxtalar', ',', 'mahsulotlarning', 'o‘ziga', 'xos', 'qorishiq', 'isi', '…']", 'pos_tags': '[0, 7, 12, 15, 7, 12, 7, 10, 0, 0, 7, 12]' } ``` ### Data Fields The data fields are the same among all splits: - `id` (`string`): ID of the example. - `tokens` (`list` of `string`): Tokens of the example text. - `pos_tags` (`list` of class labels): POS tags of the tokens, with possible values: - 0: `ADJ` - 1: `ADP` - 2: `ADV` - 3: `AUX` - 4: `CCONJ` - 5: `DET` - 6: `INTJ` - 7: `NOUN` - 8: `NUM` - 9: `PART` - 10: `PRON` - 11: `PROPN` - 12: `PUNCT` - 13: `SCONJ` - 14: `SYM` - 15: `VERB` - 16: `X` ### Data Splits Dataset consists of two splits according to its written script. | name | | |-----------------|--------:| | latin | 500 | | cyrillic | 500 | ## Dataset Creation ### Source Data * news articles: * [Kun.uz](https://kun.uz/) * [Daryo.uz](https://daryo.uz/) * fictional books: * _“Og‘riq Tishlar”_ and _“Dahshat”_ by Abdulla Qahhor * _“Shum Bola”_ and _“Yodgor”_ by G‘afur G‘ulom * _“Sofiya”_, _“Hazrati Hizr Izidan”_, _“Bibi Salima va Boqiy Darbadar”_, _“Olisdagi Urushning Aks-Sadosi”_ and _“Genetik”_ by Isajon Sulton * _“Buxoro, Buxoro, Buxoro. . . ”_, _“Ozodlik”_ and _“Lobarim Mening. . . ”_ by Javlon Jovliyev * _“Ko‘k Tog‘”_, _“Insonga Qulluq Qiladurmen”_, _“Fano va Baqo”_ and _“Chodirxayol”_ by Asqar Muxtor * _“Ajinasi Bor Yo‘llar”_ by Anvar Obidjon * _“Kecha va Kunduz”_ and _“Qor Qo‘ynida Lola”_ by Cho‘lpon. #### Initial Data Collection and Normalization All sentences were handpicked to ensure the quality of the data. ### Annotations #### Annotation process Manual #### Who are the annotators? [Arofat Akhundjanova (M.Sc. Language Science and Technology, Saarland University)](https://github.com/comp-linguist) ### Citation Information ``` @inproceedings{bobojonova-etal-2025-bbpos, title = "{BBPOS}: {BERT}-based Part-of-Speech Tagging for {U}zbek", author = "Bobojonova, Latofat and Akhundjanova, Arofat and Ostheimer, Phil Sidney and Fellenz, Sophie", editor = "Hettiarachchi, Hansi and Ranasinghe, Tharindu and Rayson, Paul and Mitkov, Ruslan and Gaber, Mohamed and Premasiri, Damith and Tan, Fiona Anting and Uyangodage, Lasitha", booktitle = "Proceedings of the First Workshop on Language Models for Low-Resource Languages", month = jan, year = "2025", address = "Abu Dhabi, United Arab Emirates", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2025.loreslm-1.23/", pages = "287--293", abstract = "This paper advances NLP research for the low-resource Uzbek language by evaluating two previously untested monolingual Uzbek BERT models on the part-of-speech (POS) tagging task and introducing the first publicly available UPOS-tagged benchmark dataset for Uzbek. Our fine-tuned models achieve 91{\%} average accuracy, outperforming the baseline multi-lingual BERT as well as the rule-based tagger. Notably, these models capture intermediate POS changes through affixes and demonstrate context sensitivity, unlike existing rule-based taggers." } ```