Abstract

Computational linguistics can offer tools for automatic grading of written texts. “Evaluator” is such a tool. It uses FreeLing as a morpho-syntactic analyzer, providing words, lemmas, and part of speech tags for each word in a text. Multi-words can also be identified and their grammar identified. “Evaluator” also manages leveled glossaries, like the one developed by the Instituto Cervantes, as well as other electronically available dictionaries. All these glossaries enable the tool to identify most words in texts, grading them into the six levels scale of the Common European Framework of Reference for Languages. To assign a lexical level to the text under analysis, a statistical distribution of leveled qualified lemmas is used. Other ways to assign a lexical level to a text by using corpora of a preset level are also suggested. The syntactic analysis is based on a collection of grammar structures leveled by following the descriptors given by the Instituto Cervantes. These grammar structures are identified within the text using quantitative indices which level a text by comparing it with a given corpus. Finally, semantic identification is done using semantic fields as defined by the Instituto Cervantes. Latent Semantic Analysis is also used to group texts dealing with the same topic together. All these methods have been tested and applied to real texts written in Spanish by native speakers and learners.

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