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--- |
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language: |
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- hy |
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license: |
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- apache-2.0 |
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multilinguality: |
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- monolingual |
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task_categories: |
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- token-classification |
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task_ids: |
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- named-entity-recognition |
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--- |
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## Table of Contents |
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- [Table of Contents](#table-of-contents) |
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- [pioNER - named entity annotated datasets](#pioNER---named-entity-annotated-datasets) |
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- [Silver-standard dataset](#silver-standard-dataset) |
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- [Gold-standard dataset](#gold-standard-dataset) |
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# pioNER - named entity annotated datasets |
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pioNER corpus provides gold-standard and automatically generated named-entity datasets for the Armenian language. |
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Alongside the datasets, we release 50-, 100-, 200-, and 300-dimensional GloVe word embeddings trained on a collection of Armenian texts from Wikipedia, news, blogs, and encyclopedia. |
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## Silver-standard dataset |
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The generated corpus is automatically extracted and annotated using Armenian Wikipedia. We used a modification of [Nothman et al](https://www.researchgate.net/publication/256660013_Learning_multilingual_named_entity_recognition_from_Wikipedia) and [Sysoev and Andrianov](http://www.dialog-21.ru/media/3433/sysoevaaandrianovia.pdf) approaches to create this corpus. This approach uses links between Wikipedia articles to extract fragments of named-entity annotated texts. |
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The corpus is split into train and development sets. |
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*Table 1. Statistics for pioNER train, development and test sets* |
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| dataset | #tokens | #sents | annotation | texts' source | |
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|-------------|:--------:|:-----:|:--------:|:-----:| |
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| train | 130719 | 5964 | automatic | Wikipedia | |
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| dev | 32528 | 1491 | automatic | Wikipedia | |
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| test | 53606 | 2529 | manual | iLur.am | |
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## Gold-standard dataset |
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This dataset is a collection of over 250 news articles from iLur.am with manual named-entity annotation. It includes sentences from political, sports, local and world news, and is comparable in size with the test sets of other languages (Table 2). |
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We aim it to serve as a benchmark for future named entity recognition systems designed for the Armenian language. |
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The dataset contains annotations for 3 popular named entity classes: |
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people (PER), organizations (ORG), and locations (LOC), and is released in CoNLL03 format with IOB tagging scheme. |
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During annotation, we generally relied on categories and [guidelines assembled by BBN](https://catalog.ldc.upenn.edu/docs/LDC2005T33/BBN-Types-Subtypes.html) Technologies for TREC 2002 question answering track |
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Tokens and sentences were segmented according to the UD standards for the Armenian language from [ArmTreebank project](http://armtreebank.yerevann.com/tokenization/process/). |
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*Table 2. Comparison of pioNER gold-standard test set with test sets for English, Russian, Spanish and German* |
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| test dataset | #tokens | #LOC | #ORG | #PER | |
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|-------------|:--------:|:-----:|:--------:|:-----:| |
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| Armenian pioNER | 53606 | 1312 | 1338 | 1274 | |
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| Russian factRuEval-2016 | 59382 | 1239 | 1595 | 1353 | |
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| German CoNLL03 | 51943 | 1035 | 773 | 1195 | |
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| Spanish CoNLL02 | 51533 | 1084 | 1400 | 735 | |
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| English CoNLL03 | 46453 | 1668 | 1661 | 1671 | |
