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This paper presents an automated natural language question generator for Tagalog informational texts. It takes a target text as an input and generates a set of what, where and who question and answer pairs extracted from the source text. The resulting questions are also ranked using a proposed acceptability criterion. The implementation consists of three modules: a part of speech tagger, an anaphora resolver, and a question ranker. Questions generated from the experiment were rated by three evaluators. Of the generated questions, 33% were rated as acceptable by the evaluators, 96% of which were in need of modifications.
Montenegro et al. (Thu,) studied this question.