The article presents a method for automatic semantic indexing of archaeological grey‐literature reports using empirical (rule‐based) Information Extraction techniques in combination with domain‐specific knowledge organization systems. The semantic annotation system (OPTIMA) performs the tasks of Named Entity Recognition, Relation Extraction, Negation Detection, and Word‐Sense Disambiguation using hand‐crafted rules and terminological resources for associating contextual abstractions with classes of the standard ontology CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM‐EH. Relation Extraction (RE) performance benefits from a syntactic‐based definition of RE patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive natural language processing (NLP) modules relating to Word‐Sense Disambiguation, Negation Detection, and Noun Phrase Validation, together with controlled thesaurus expansion.
The semantic indexing results demonstrate the capacity of rule‐based Information Extraction techniques to deliver interoperable semantic abstractions (semantic annotations) with respect to the CIDOC CRM and archaeological thesauri. Major contributions include recognition of relevant entities using shallow parsing NLP techniques driven by a complimentary use of ontological and terminological domain resources and empirical derivation of context‐driven RE rules for the recognition of semantic relationships from phrases of unstructured text.
CrossCult is an EU-funded research project aiming to spur a change in the way European citizens appraise History, fostering the re-interpretation of what they may have learnt in the light of cross-border interconnections among pieces of cultural heritage, other citizens' viewpoints and physical venues. Exploiting the expressive power, reasoning and interoperability capabilities of semantic technologies, the CrossCult Knowledge Base models and semantically links desperate pieces of Cultural Heritage information, contributing significantly to the aims of the project. This paper presents the structure, design rationale and development of the CrossCult Knowledge Base, aiming to inform researchers in Digital Heritage about the challenges and opportunities of semantically modelling Cultural Heritage data.
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