Remarks on separating words

The separating words problem asks for the size of the smallest DFA needed to distinguish between two words of length <= n (by accepting one and rejecting the other). In this paper we survey what is known and unknown about the problem, consider some variations, and prove several new results

Predicting Morphologically-Complex Unknown Words in Igbo

The effective handling of previously unseen words is an important factor in the performance of part-of-speech taggers. Some trainable POS taggers use suffix (sometimes prefix) strings as cues in handling unknown words (in effect serving as a proxy for actual linguistic affixes). In the context of creating a tagger for the African language Igbo, we compare the performance of some existing taggers, implementing such an approach, to a novel method for handling morphologically complex unknown words, based on morphological reconstruction (i.e. a linguistically-informed segmentation into root and affixes). The novel method outperforms these other systems by several percentage points, achieving accuracies of around 92 % on morphologically-complex unknown words