Towards light semantic processing for Question Answering

The paper presents a lightweight knowledge-based reasoning framework for the JAVELIN open-domain Question Answering (QA) system. We propose a constrained representation of text meaning, along with a flexible unification strategy that matches questions with retrieved passages based on semantic similarities and weighted relations between words.