6 research outputs found
Can BERT Dig It? -- Named Entity Recognition for Information Retrieval in the Archaeology Domain
The amount of archaeological literature is growing rapidly. Until recently,
these data were only accessible through metadata search. We implemented a text
retrieval engine for a large archaeological text collection ( Million
words). In archaeological IR, domain-specific entities such as locations, time
periods, and artefacts, play a central role. This motivated the development of
a named entity recognition (NER) model to annotate the full collection with
archaeological named entities. In this paper, we present ArcheoBERTje, a BERT
model pre-trained on Dutch archaeological texts. We compare the model's quality
and output on a Named Entity Recognition task to a generic multilingual model
and a generic Dutch model. We also investigate ensemble methods for combining
multiple BERT models, and combining the best BERT model with a domain thesaurus
using Conditional Random Fields (CRF). We find that ArcheoBERTje outperforms
both the multilingual and Dutch model significantly with a smaller standard
deviation between runs, reaching an average F1 score of 0.735. The model also
outperforms ensemble methods combining the three models. Combining ArcheoBERTje
predictions and explicit domain knowledge from the thesaurus did not increase
the F1 score. We quantitatively and qualitatively analyse the differences
between the vocabulary and output of the BERT models on the full collection and
provide some valuable insights in the effect of fine-tuning for specific
domains. Our results indicate that for a highly specific text domain such as
archaeology, further pre-training on domain-specific data increases the model's
quality on NER by a much larger margin than shown for other domains in the
literature, and that domain-specific pre-training makes the addition of domain
knowledge from a thesaurus unnecessary
User Requirement Solicitation for an Information Retrieval System Applied to Dutch Grey Literature in the Archaeology Domain
In this paper, we present the results of user requirement solicitation for a search system of grey literature in archaeology, specifically Dutch excavation reports. This search system uses Named Entity Recognition and Information Retrieval techniques to create an effective and effortless search experience. Specifically, we used Conditional Random Fields to identify entities, with an average accuracy of 56%. This is a baseline result, and we identified many possibilities for improvement. These entities were indexed in ElasticSearch and a user interface was developed on top of the index. This proof of concept was used in user requirement solicitation and evaluation with a group of end users. Feedback from this group indicated that there is a dire need for such a system, and that the first results are promising
Excavation of the late Mesolithic site of Merselo-Haag (Venray)
Opgravingsdocumentatie en artefactbeschrijvingen van de Merselo-Haag. De databestanden van de opgraving omvatten verspreidingskaarten en beschrijving van het vuursteen-vondstmateriaal.Excavation documentation and artefact analysis. The files of the excavation Merselo-Haag contain spatial distributions and artefact descriptions, mainly of flint artefact