DOI: 10.35111/t5qx-jc85
title: LoReHLT Uzbek Representative Language Pack

description: <h3>Introduction</h3>
<p>LoReHLT Uzbek Representative Language Pack (LDC2025T08) consists of Uzbek monolingual text, Uzbek-English parallel text, annotations, amateur web audio recordings, supplemental resources and related software tools developed by the Linguistic Data Consortium for LoReHLT, a companion project of the DARPA LORELEI program.</p>
<p>The LORELEI (Low Resource Languages for Emergent Incidents) program was concerned with building human language technology for low resource languages in the context of emergent situations like natural disasters or disease outbreaks. Linguistic resources for LORELEI include Representative Language Packs and Incident Language Packs for over two dozen low resource languages, comprising data, annotations, basic natural language processing tools, lexicons and grammatical resources. Representative languages were selected to provide broad typological coverage, while incident languages were selected to evaluate system performance on a language whose identity was disclosed at the start of the evaluation.</p>
<h3>Data</h3>
<p>Uzbek is spoken across central Asia; it is the official language in Uzbekistan. </p>
<p>This release is the result of a pilot effort preceding the LORELEI program. Text data was collected in the following genres: news, discussion forum, reference, social network, and weblogs. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods. Also collected were amateur web audio recordings related to disaster events that were covered in the text data. </p>
<p>Data volumes are as follows:</p>
<ul>
<li>47 million words of Uzbek monolingual text, over 886,000 of which were translated into English</li>
<li>663,000 Uzbek words translated from English data</li>
<li>6.41 hours of Uzbek audio recordings</li>
</ul>
<p>Approximately 151,000 words were annotated for named entities, and over 28,000 words were annotated for full entity including nominals and pronouns. Noun-phrase chunking was applied to more than 13,000 words. Over 20,890 words were labeled with simple semantic annotation. Topic annotation was applied to the audio recordings.</p>
<p>Lexical resources and software tools are also included in this release. The tools recreate original source data from the processed XML material, condition text data users download from Twitter, apply sentence segmentation to raw text, and support named entity tagging.</p>
<p>Monolingual and parallel text are presented in XML with associated dtds. Annotation data is presented as tab delimited files or XML. All text is UTF-8 encoded. The audio recordings are presented in FLAC-compressed MS-WAV and .mp4 format.</p>
<p>The knowledge base for entity linking annotation for this corpus and all LORELEI Representative Language and Incident Language Packs is available separately as <a href="../../../LDC2020T10">LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10)</a>.</p>
<h3>Sponsorship</h3>
<p>This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA) under Contract No. HR0011-15-C-0123. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of DARPA.</p>
<h3>Updates</h3>
<p>No updates at this time.</p>
<p> </p>