DOI: 10.35111/6pzy-pq94
title: LORELEI Amharic Representative Language Pack - Monolingual and Parallel Text

description: <h3>Introduction</h3><br>
<p>LORELEI Amharic Representative Language Pack - Monolingual and Parallel Text was developed by the Linguistic Data Consortium and is comprised of approximately 25 million words of monolingual Amharic text, approximately 600,000 of which are translated into English. Another 80,000 words are also translated from English into Amharic.</p><br>
<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><br>
<h3>Data</h3><br>
<p>Data was collected in the following genres: discussion forums, news, reference, social network and weblog. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods, which are detailed in the included documentation. All harvested content was initially converted from its original HTML form into a relatively uniform XML format.</p><br>
<p>XML data is presented in two formats: a "homogenized" XML format that preserves the minimum set of tags needed to represent the structure of the relevant text as seen by the human web-page reader and a fully segmented and tokenized version of the text. All text data is encoded as UTF-8.</p><br>
<p>Also included in this release are two tools: one to recreate original source data from the processed XML material and the other to condition text data users download from Twitter.</p><br>
<h3>Acknowledgement</h3><br>
<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><br>
<h3>Samples</h3><br>
<p>Please view this <a href="desc/addenda/LDC2018T04.amh.ltf.xml">Amharic sample</a> and <a href="desc/addenda/LDC2018T04.eng.ltf.xml">English translation sample</a>.</p><br>
<h3>Updates</h3><br>
<p>None at this time.</p></br>
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