Automatic identification of nocuous ambiguity

We present the concept of nocuous ambiguity, which occurs when text is interpreted differently by different readers. In contrast, text exhibits innocuous ambiguity if different readers interpret it in the same way, even though structural or semantic analyses suggest that multiple interpretations may be possible. We collect multiple human judgements of a set of English phrases obtained from requirements documents. We focus on coordination ambiguity and show that across a group of judges there may be wide variation in what is perceived to be the correct interpretation. We develop the concept of an ambiguity threshold, which expresses the amount of variation between judgements that can be tolerated. We then develop and evaluate a heuristically based method of automatically predicting which sentences may be misunderstood for a given ambiguity threshold