Ontology-based semantic interpretation framework for legal analysis of construction claims

Currently the two main obstacles limiting the performance of legal analysis in construction claims are: the scarcity of knowledge of contractual and claim knowledge on the construction project job-site, and the inefficiency of manual processing vast amount of raw records about the history of a claim case. A lot of research has been done in this area, however, the methodologies used thus far for knowledge representation and sharing suffered from inherent drawbacks, and almost none of them took into consideration the automatic semantic interpretation of the text for claim case history. To address these two problems, an ontology-based semantic interpretation framework is proposed in this study. In this framework, ontology is used to represent the domain knowledge for claim analysis and a synthesized methodology is conceived for ontology development. Furthermore, the framework prototype for utilizing ontology in legal analysis in construction claims and a rule-based Natural Language Processing (NLP) methodology for capturing the mapping between ontology and language elements are also proposed. The framework is able to provide the functionality for the semantic interpretation of impact factors in the claim history text of a project. In order to validate the proposed methodologies and framework, two case studies were conducted. The first one was using the synthesized ontology development methodology to develop an ontology taxonomy on the contractual semantics of the AIA A201 General Conditions of the Contract for Construction (2007). Based on the proposed framework, the second case study implemented an application for the functionality of the semantic interpretation of impact factors in Differing Site Conditions (DSC) Type I claim cases. This application uses a rule-based system which mainly adopts information extraction in NLP and ontology together to determine the existence of an impact factor in the claim history text of a project. Overall, this study develops a novel way of dealing with the two above-mentioned obstacles to improving the effectiveness and efficiency of legal analysis of construction contractual claims. The results determined that the body of knowledge about construction contract and claim analysis can be conceptualized and formalized into an ontology, and this ontology can be used together with NLP technology to enable semantic interpretation for assisting legal analysis in construction claim cases at the textual level.