Authors: Jennifer Tracey, Stephanie Strassel, David Graff, Jonathan Wright, Song Chen, Neville Ryant, Seth Kulick, Kira Griffitt, Dana Delgado, Michael Arrigo.
Data source: discussion forum, newswire, web collection, weblogs.
Data type: software, text.
Applications: cross-language transfer, entity extraction, information extraction, machine translation.
LDC number: LDC2024T01.
"Farsi is spoken mainly in Iran and Afghanistan; it is the official language in both countries. Data was collected in the following genres: discussion forum, news, reference, social network, and weblogs. Both monolingual text collection and parallel text creation involved a combination of manual and automatic methods. Data volumes are as follows: 250 million words of Farsi monolingual text, over 391,000 of which were translated into English -- 751,000 words of found Farsi-English parallel text -- 120,000 Farsi words translated from English data. Approximately 75,000 words are annotated for named entities, and over 22,000 words were annotated for full entity including nominals and pronouns, simple semantic annotation, situation frame annotation, and entity linking. 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. 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 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)."--LDC online catalog.
In Persian and English.
Title from resource home page (LDC website, viewed February 19, 2024).