We present an open source, freely available Java implementation of Align, Disambiguate, and Walk (ADW), a state-of-the-art approach for measuring semantic similarity based on the Personalized PageRank algorithm. A pair of linguistic items, such as phrases or sentences, are first disambiguated using an alignment-based disambiguation technique and then modeled using random walks on the WordNet graph. ADW provides three main advantages: (1) it is applicable to all types of linguistic items, from word senses to texts; (2) it is all-in-one, i.e., it does not need any additional resource, training or tuning; and (3) it has proven to be highly reliable at different lexical levels and multiple evaluation benchmarks. We are releasing the source code at https://github.com/pilehvar/adw/. We also provide at http://lcl.uniroma1.it/adw/ a Web interface and a Java API that can be seamlessly integrated into other NLP systems requiring semantic similarity measurement.
['Mohammad Taher Pilehvar', 'Roberto Navigli']
An Open-source Framework for Multi-level Semantic Similarity Measurement