Natural language processing applications have an important role in our daily life, by enablingrncomputers to understand human languages. NLP applications such as machine translation,rnquestion answering, knowledge extraction and information retrieval are among the most commonrnapplications which we need to accomplish different tasks. For better development of the abovernmentioned applications the assigning of part of speech of words, the extraction of phrases andrnsub-phrases, and the extraction of syntactic structure of sentences from natural language texts arernimportant. Amharic is one of the under resourced languages whose natural language tools andrnapplications are not yet built successfully. Therefore, parsing Amharic sentences is a necessaryrnmechanism for many applications. Sentence parsing is one of the tasks of NLP tools whichrnidentify the syntactic structure of a specific sentence according to the grammar of a language.rnFor this reason, many natural language applications underlie on sentence parser for betterrnperformance.rnFor foreign languages like English and Arabic, many sentences parsers are developed in differentrnapproaches. However in the case of Amharic, there are few works done which still requirernimprovements and additional features. In addition, they are conducted in small dataset onrnspecific types of sentences.rnIn our study, we have designed a similar system to parse all types of Amharic sentences using arntop-down chart parsing algorithm using Context Free Grammar to represent the Amharicrngrammars. We have developed a lexicon generator to automatically generate the lexicon which isrnseparated from the CFG. In addition, we have integrated a morphological analyzer in thernconstruction of the lexicon. The main purpose of the morphological analyzer is to reduce thernnumber of words required to be stored in the lexicon. The morphological analyzer results thernmorpheme of the given words so that words which have common root are represented by theirrnmorpheme in the lexicon. The parser is tested on test sentences which are extracted fromrndifferent sources. Experimental results showed the effectiveness of the proposed parser.rnKeywords: NLP, Parser, context free grammar, top-down chart parser, lexicon generator,rnlexicon, morphological analyzer.