TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay

摘要

When tweeting on a topic, Twitter users often post messages that convey the same or similar meaning. We describe Tweeting Jay, a system for detecting paraphrases and semantic similarity of tweets, with which we participated in Task 1 of SemEval 2015. Tweetingjay uses a supervised model that combines semantic overlap and word alignment features, previously shown to be effective for detecting semantic textual similarity. Tweetingjay reaches 65.9% F1-score and ranked fourth among the 18 participating systems. We additionally provide an analysis of the dataset and point to some peculiarities of the evaluation setup.