A Method for Archaeological and Dendrochronological Concept Annotation using Domain Knowledge in Information Extraction

Advances in Natural Language Processing allow the process of deriving information from large volumes of text to be automated. Attention is turned to one of the most important, but traditionally difficult to access resources in archaeology, commonly known as “grey literature”. This paper presents the development of two separate Named-Entity Recognition (NER) pipelines aimed at the extraction of Archaeological and of Dendrochronological concepts in Dutch, respectively. The role of domain vocabulary is discussed for the development of a Knowledge Organization System (KOS)-driven, Rule-Based method of NER which makes complementary use of ontology, thesauri and domain vocabulary for information extraction and attribute assignment of semantic annotations. The NER task is challenged by a series of domain and language-oriented aspects and evaluated against a human-annotated Gold Standard. The results suggest the suitability of Rule-based KOS driven approaches for attaining the low-hanging fruits of NER, using a combination of quality vocabulary and rules.