: Sentence Similarity from Word Alignment

We present an algorithm for computing the semantic similarity between two sen-tences. It adopts the hypothesis that se-mantic similarity is a monotonically in-creasing function of the degree to which (1) the two sentences contain similar se-mantic units, and (2) such units occur in similar semantic contexts. With a simplis-tic operationalization of the notion of se-mantic units with individual words, we ex-perimentally show that this hypothesis can lead to state-of-the-art results for sentence-level semantic similarity. At the Sem-Eval 2014 STS task (task 10), our system demonstrated the best performance (mea-sured by correlation with human annota-tions) among 38 system runs.