**Introduction** LORELEI Arabic Representative Language Pack (LDC2026T08) consists of Arabic monolingual text, Arabic-English parallel text, annotations, supplemental resources and related software tools developed by the Linguistic Data Consortium for the DARPA LORELEI program. 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. **Data** Arabic is spoken throughout the Middle East and North Africa and is an official language in more than 20 countries. Data was collected in the following genres: discussion forum, news, weblogs and social network. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods. Data volumes are as follows: 2.4 million words of Arabic monolingual text, over 930,000 words of which were translated into English 225,000 Arabic words translated from English data Nearly 88,000 words were annotated for simple named entities, and approximately 29,000 words were annotated for full entities (including nominals and pronouns). In addition, over 10,000 words were annotated for noun phrase chunking, 18,000 words were labeled with semantic annotation and situation frame annotation was applied to more than 24,000 words. 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/X, apply sentence segmentation to raw text, and support named entity tagging. Monolingual and parallel text are presented in XML with associated DTDs. Annotation data is presented as XML or tab-delimited files. All text is UTF-8 encoded. The knowledge base for entity linking annotation for this corpus and all LORELEI Representative Language and Incident Language Packs is available separately as LORELEI Entity Detection and Linking Knowledge Base (LDC2020T10). **Sponsorship** 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. **Updates** No updates at this time.

Creator(s)

Jennifer Tracey

Stephanie Strassel

David Graff

Jonathan Wright

Song Chen

Neville Ryant

Seth Kulick

Kira Griffitt

Dana Delgado

Michael Arrigo

Distributor(s)

Linguistic Data Consortium

Right Holder(s)

Linguistic Data Consortium