The paper presents a semantic annotation framework that is capable of extracting relevant
information from unstructured, ungrammatical and incoherent data sources. The framework,
named BNOSA, uses ontology to conceptualize a problem domain and to extract data from
the given corpora, and Bayesian networks to resolve conflicts and to predict missing data.
The framework is extensible as it is capable of dynamically extracting data from any problem
domain given a pre-defined ontology and a corresponding Bayesian network. Experiments …