Knowledge-Based Named Entity Recognition of Archaeological Concepts in Dutch

Andreas Vlachidis, Douglas Tudhope, Milco Wansleeben

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The advancement of Natural Language Processing (NLP) allows the process of deriving information from large volumes of text to be automated, making text-based resources more discoverable and useful. The attention is turned to one of the most important, but traditionally difficult to access resources in archaeology; the largely unpublished reports generated by commercial or “rescue” archaeology, commonly known as “grey literature”. The paper presents the development and evaluation of a Named Entity Recognition system of Dutch archaeological grey literature targeted at extracting mentions of artefacts, archaeological features, materials, places and time entities. The role of domain vocabulary is discussed for the development of a KOS-driven NLP pipeline which is evaluated against a Gold Standard, human-annotated corpus.
Original languageEnglish
Title of host publicationCommunications in Computer and Information Science
Subtitle of host publicationMetadata and Semantic Research. MTSR 2020
EditorsEmmanouel Garoufallou, María-Antonia Ovalle-Perandones
Place of PublicationCham
PublisherSpringer
Pages53-64
Number of pages12
Volume1335
ISBN (Electronic)978-3-030-71903-6
ISBN (Print)978-3-030-71902-9978-3-030-71903-6
DOIs
Publication statusPublished - 21 Mar 2021
EventMetadata and Semantic Research, 14th International Conference (2020) - Madrid, Spain
Duration: 2 Dec 20204 Dec 2020
Conference number: 14

Publication series

NameCommunications in Computer and Information Science
PublisherSpringer
Volume1355
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

ConferenceMetadata and Semantic Research, 14th International Conference (2020)
Abbreviated titleMTSR 2020
Country/TerritorySpain
CityMadrid
Period2/12/204/12/20

Keywords

  • named entity recognition
  • archaeology
  • grey literature
  • CIDOC-CRM
  • Knowledge Organization Systems

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