Create README.md

README.md

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+---
+YAML tags:
+languages: [hy]
+task_categories: [named-entity-recognition]
+multilinguality: [monolingual]
+task_ids: [named-entity-recognition]
+licenses: [apache-2.0]
+---
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [pioNER - named entity annotated datasets and GloVe models for the Armenian language](#pioNER)
+  - [Silver-standard dataset](#silver-standard-dataset)
+  - [Gold-standard dataset](#gold-standard-dataset)
+
+
+
+# pioNER - named entity annotated datasets and GloVe models for the Armenian language
+
+pioNER corpus provides gold-standard and automatically generated named-entity datasets for the Armenian language.
+
+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.
+
+## Silver-standard dataset
+
+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.
+
+The corpus is split into train and development sets. 
+
+*Table 1. Statistics for pioNER train, development and test sets*
+
+| dataset       | #tokens | #sents | annotation | texts' source |
+|-------------|:--------:|:-----:|:--------:|:-----:|
+| train    | 130719 |  5964  | automatic | Wikipedia |
+| dev | 32528 | 1491 | automatic | Wikipedia |
+| test | 53606 | 2529 | manual | iLur.am |
+
+## Gold-standard dataset
+
+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). 
+We aim it to serve as a benchmark for future named entity recognition systems designed for the Armenian language.
+
+The dataset contains annotations for 3 popular named entity classes: 
+people (PER), organizations (ORG), and locations (LOC), and is released in CoNLL03 format with IOB tagging scheme. 
+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
+
+Tokens and sentences were segmented according to the UD standards for the Armenian language from [ArmTreebank project](http://armtreebank.yerevann.com/tokenization/process/).
+
+*Table 2. Comparison of pioNER gold-standard test set with test sets for English, Russian, Spanish and German*
+
+| test dataset       | #tokens | #LOC | #ORG | #PER |
+|-------------|:--------:|:-----:|:--------:|:-----:|
+| Armenian pioNER    | 53606 |  1312  | 1338 | 1274 |
+| Russian factRuEval-2016 | 59382 | 1239 | 1595 | 1353 |
+| German CoNLL03 | 51943 | 1035 | 773 | 1195 |
+| Spanish CoNLL02 | 51533 | 1084 | 1400 | 735 |
+| English CoNLL03 | 46453 | 1668 | 1661 | 1671 |