Contemporary Amharic Corpus: Automatically Morpho-Syntactically Tagged Amharic Corpus
This provides a valuable resource for NLP researchers and developers working on Amharic language processing, though it is incremental as it builds on existing tools and methods.
The authors tackled the lack of a large, tagged corpus for Amharic by creating a contemporary corpus with 24 million words from 25,199 documents, automatically tagged for morpho-syntactic information using a modified version of HornMorpho.
We introduced the contemporary Amharic corpus, which is automatically tagged for morpho-syntactic information. Texts are collected from 25,199 documents from different domains and about 24 million orthographic words are tokenized. Since it is partly a web corpus, we made some automatic spelling error correction. We have also modified the existing morphological analyzer, HornMorpho, to use it for the automatic tagging.