The Semantics of Negation Detection in Archaeological Grey Literature
Archaeological reports contain a great deal of information that conveys facts and findings in different ways. This kind of information is highly relevant to the research and analysis of archaeological evidence but at the same time can be a hindrance for the accurate indexing of documents with respect to positive assertions. The paper presents a method for adapting the biomedicine oriented negation algorithm NegEx to the context of archaeology and discusses the evaluation results of the new modified negation detection module. The performance of the module is compared against a “Gold Standard” and evaluation results are encouraging, delivering overall 89% Precision, 80% Recall and 83% F-Measure scores. The paper addresses limitations and future improvements of the current work and highlights the need for ontological modelling to accommodate negative assertions. It concludes that adaptation of the NegEx algorithm to the archaeology domain is feasible and that rule-based information extraction techniques are capable of identifying a large portion of negated phrases from archaeological grey literature.
KeywordsNegation Detection Semantic Technologies Digital Humanities CIDOC-CRM Semantic Annotation Natural Language Processing
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