Extracting Proper nouns in Electronically English and Arabic Texts. Theoretical Background and Practices (PDF)

Project Report from the year 2018 in the subject Computer Sciences - Computational linguistics, grade: 16/20, Lebanese International University, language: English, abstract: Before starting the research for the ways to extract proper nouns, we should ask ourselves what is proper noun. According to British council learning center, proper nouns are the names of organizations including companies, places, and people. However, what is the benefit of proper nouns? They give the reader a surface knowledge of what is going on in any given content. Sometimes, the text or sentence is worthless without the specific nouns, which include. People usually read articles for the famous people, places, or organizations they speak about.

Many studies in English language have been conducted in the Name recognition of proper nouns while in Arabic it is still at its early stages. The coding files can meet the goal of extracting proper nouns but not even close to 100% accuracy. By the use of modules that understand the sentence structure as Lingua::EN::NamedEntity, the result would score a higher accuracy, however, does not achieve a satisfactory results. In addition, the Arabic systems of its both methods: rule-based or machine learning are still no comparable to systems that have been developed in the English language, which opens a wide scope for researches to work on NERA (Name Entity Recognition in Arabic language).