Towards a thematic role based target identification model for question answering

Target identification plays a crucial role in web based question answering. But still current approaches are not matured enough to extract the exact target of any given question and therefore leads the system to low precision. To address this gap in the current researches we propose thematic role based methodology to extract the target type of the question. Proposed solution is fully wrapped in the shallow semantic processing of the question rather directing it to the deep parsing. Research employs dative alternation of the question thus providing strict rule based approaches to be implemented to elicit the target with high confidence. Furthermore, the proposed solution can be extended with semantically rich target types by mapping concepts identified in question to semantic categories. This extensibility exhibits that our new approach is scalable and can be tweaked to achieve high precision level that current methods are incapable to achieve.