Recognizing Textual Entailment with a Semantic Edit Distance Metric

We present a Recognizing Textual Entailment(RTE) system based on different similarity metrics. The metrics used are string-based metrics and the Semantic Edit Distance Metric, which is proposed in this paper to address limitations of known semantic-based metrics and to support the decisions made by a simple method based on lexical similarity metrics.We add the scores of the metrics as features for a machine learning algorithm. The performance of our system is comparable with the average performance of the Recognizing Textual Entailment Challenges, though lower than that of the state-of-the-art methods.