EAL: A Toolkit and Dataset for Entity-Aspect Linking

We present a toolkit and dataset for entity-aspect linking. The tool takes as input a sentence and provides the most relevant aspect for each mentioned entity; it is implemented in Python and available as a script and via an online demo. It is accompanied by the first large dataset of entity-aspects, comprising more than 20,000 entities manually linked to the most relevant aspect, given a sentence as context. Each is expressed in structured manner as Open Information Extraction (OIE) triples (Subject, Relation, Object), having semantic information for polarity, modality, quantity and attributions.