Morphologically Annotated Amharic Text Corpora

Abstract

In information retrieval (IR), documents that match the query are retrieved. Search engines usually conflate word variants into a common stem when indexing documents because queries and documents do not need to use exactly the same word variant for the documents to be relevant. Stemmers are known to be effective in many languages for IR. However, there are still languages where stemmers or morphological analyzers are missing; this is the case for Amharic which is the working language of Ethiopia. Morphological analysis is the key to derive stems, roots (primary lexical units) and grammatical markers of words such as person, tense and negation markers. This paper presents morphologically annotated Amharic lexicons as well as stem-based and root-based morphologically annotated corpora which could be used by the research community as benchmark collections either to evaluate morphological analyzers or information retrieval for Amharic. Such resources are believed to foster research in Amharic IR.

Amharic Semantic Information Retrieval System

“…We can quote a few such studies. Demeke and Getachew [23] created Walta Information Center news corpus; Yeshambel et al [24] built 2AIRTC; and Yeshambel et al [10] created stem-based and root-based morphologically annotated Amharic corpora semiautomatically. The sizes of corpora created by Demeke and Getachew [23], Yeshambel et al [24] and Yeshambel et al [10] are 1,065, 12,586, and 6,069 documents, respectively.…”

“…Demeke and Getachew [23] created Walta Information Center news corpus; Yeshambel et al [24] built 2AIRTC; and Yeshambel et al [10] created stem-based and root-based morphologically annotated Amharic corpora semiautomatically. The sizes of corpora created by Demeke and Getachew [23], Yeshambel et al [24] and Yeshambel et al [10] are 1,065, 12,586, and 6,069 documents, respectively. Mindaye et al [13] and Samuel and Bjorn [25] created Amharic word-based stopword list whereas Alemayehu and Willett [26] built stem-based stopwords list.…”

“…stem and root) could be extracted easily and quickly. The two morphological analyses performed in this work are stem-based and root-based morphological analysis using lexicons created by Yeshambel et al [10]. The lexicons are constructed from a corpus.…”

“…In this work, Amharic surface words are segmented into their morphemes by analyzing the internal structure of words and their contexts. The annotation is made semi-automatically using Amharic lexicons built by Yeshambel et al [10]. For comparison of stem-based and root-based text representations, we created the stem-based and root-based corpora from the same document collection.…”

“…The existing Amharic IR systems face challenges in searching relevant documents because of the morphological complexity and semantic richness of the language. Amharic exhibits complex morphology that poses challenges in NLP and IR [9,10]. The base of Amharic word can be stem or root.…”