Assabie, Yaregal (PhD)Tefera, Alclgn2022-01-052023-11-042022-01-052023-11-042013-03http://etd.aau.edu.et/handle/123456789/29475Semantic networks are becoming popular issues these days. Even though this popularity is mostly related to the idea of semantic web, it is also related to the natural language applications. Semantic networks allow search engines to search nOI only for the key words given by the user but also for the related concepts. and show how this relation is made. Knowledge stored as semantic networks can he used by programs that generate text from structured data. Semantic networks are also used for document summarization by compressing the data semantically and document classification using the knowledge stored in it. As a result, semantic networks have become key components in many NLP applications. In this thesis, we focused on the construction of semantic networks for Amharic text. We have developed Amharic WordNet as initial knowledge base for the system and extracted intervening word patterns between pairs of concepts in the WordNet for a specific relation from free text. For each pair of concepts which we know the relationship contained in Amharic WordNet, we search the corpus for some text snapshot between these concepts. The returned text snapshot is processed to extract all the patterns having n·gram words between the two concepts. We have used the WordS pace model for extraction of semantically related concepts. The process of relation identification in among these concepts utilizes the extracted text patterns. "Part·of' and "type·of' relations are very popular and frequently found between concepts in any corpus. We have designed our system to extract "part·of' and "type·of' relations between concepts. The system was tested in three different phases with different datasets from Ethiopian News Agency and Walta Information Center. The accuracy of the system to extract pairs of concepts having "type·of' and "part-of' relations is 68.5% and 71.7% respectively.enAmharic pattern extraction. Amharic relation extraction, Amharic Semantic Network, Amharic Knowledge baseThesis