Morphological analysis with limited resources: Latvian example
Pēteris Paikens, Laura Rituma, Lauma Pretkalniņa · DSpace repository (University of Tartu) · 2013
We describe an approach for morphological analysis combining a rule-based word level morphological analyzer with statistical tagging, detailing its application to Latvian language.Latvian is a highly inflective Indo-European language with a rich morphology.The tools described here include an implementation of Latvian inflectional paradigms, a morphological analysis tool with a guessing module for out-of-vocabulary words, and a statistical POS/morphology tagger for disambiguation of multiple analysis possibilities.Currently achieved accuracy with a training set of only ~40 000 words is 97.9% for part of speech tagging and 93.6% for the full morphological feature tag set, which is better than any previously publicly available taggers for Latvian.We also describe the construction and methodology of the necessary linguistic resources -a morphological dictionary and an annotated morphological corpus, and evaluate the effect of resource size on analysis accuracy, showing what results can be achieved with limited linguistic resources.