With the increase in the number and size of computer learner corpora in the field of Second Language Acquisition, there is a growing need to automatically analyze the language produced by learners. However, the computational tools developed for natural language processing are generally not considered as appropiate because they are designed to treat native language. This paper analyzes the reliability of two part-of-speech taggers on second language Spanish and investigates the most frequent tagger errors and the impact of learner errors in the performance of the taggers.
