This paper discusses the challenges of applying named entity linking in a rich, complex domain-specifically, the linking of 1) military units, 2) places and 3) people in the context of interlinked Second World War data. Multiple sub-scenarios are discussed in detail through concrete evaluations, analyzing the problems faced, and the solutions developed. A key contribution of this work is to highlight the heterogeneity of problems and approaches needed even inside a single domain, depending on both the source data as well as the target authority.
This paper argues that representing texts as semantic Linked Data provides a useful basis for analyzing their contents in Digital Humanities research and for Cultural Heritage application development. The idea is to transform Cultural Heritage texts into a knowledge graph and a Linked Data service that can be used flexibly in different applications via a SPARQL endpoint. The argument is discussed and evaluated in the context of biographical and prosopographical research and a case study where over 13 000 life stories of the National Biography of Finland were transformed into RDF, enriched by data linking, and published in a SPARQL endpoint. Tools for biography and prosopography, data clustering, network analysis, and linguistic analysis were created with promising first results.
The Second World War (WW2) is arguably the most devastating catastrophe of human history, a topic of great interest to not only researchers but the general public. However, data about the Second World War is heterogeneous and distributed in various organizations and countries making it hard to utilize. In order to create aggregated global views of the war, a shared ontology and data infrastructure is needed to harmonize information in various data silos. This makes it possible to share data between publishers and application developers, to support data analysis in Digital Humanities research, and to develop data-driven intelligent applications. As a first step towards these goals, this article presents the WarSampo knowledge graph (KG), a shared semantic infrastructure, and a Linked Open Data (LOD) service for publishing data about WW2, with a focus on Finnish military history. The shared semantic infrastructure is based on the idea of representing war as a spatio-temporal sequence of events that soldiers, military units, and other actors participate in. The used metadata schema is an extension of CIDOC CRM, supplemented by various military history domain ontologies. With an infrastructure containing shared ontologies, maintaining the interlinked data brings upon new challenges, as one change in an ontology can propagate across several datasets that use it. To support sustainability, a repeatable automatic data transformation and linking pipeline has been created for rebuilding the whole WarSampo KG from the individual source datasets. The WarSampo KG is hosted on a data service based on W3C Semantic Web standards and best practices, including content negotiation, SPARQL API, download, automatic documentation, and other services supporting the reuse of the data. The WarSampo KG, a part of the international LOD Cloud and totalling ca. 14 million triples, is in use in nine end-user application views of the WarSampo portal, which has had over 690 000 end users since its opening in 2015.
This paper shows how named entity extraction and network analysis can be used to examine biographies individually and in groups to aid historians in biographical and prosopographical research. For this purpose a reference network of 13100 biography entries in the collections of the Biographical Centre of the Finnish Literature Society was created, based on links between the biographies as well as automatically extracted named entities found in the texts. The data was published in a SPARQL endpoint as a Linked Data knowledge graph on top of which network analytic tools were created and analysis were done showing the usefulness of the approach in Digital Humanities. The reference graph has been utilized for network analysis to examine egocentric networks of individual persons as well as networks among groups of people in prosopography. The data and tools presented are in use in the new national semantic portal BiographySampo published in the autumn of 2018.
Legislation and case law are widely published on the Web as documents for humans to read. In contrast, this poster paper argues for publishing legal documents as Linked Open Data (LOD) on top of which intelligent legal services for end users can be created in addition to just providing the documents for close reading. To test and demonstrate this idea, we present work on creating the Linked Open Data service SEMANTIC FINLEX for Finnish legislation and case law and the semantic portal prototype LAWSAMPO for serving end users with legal data. SEMANTIC FINLEX is a harmonized knowledge graph that is created automatically from legal textual documents and published in a SPARQL endpoint on top of which the various applications of LAWSAMPO are implemented. First applications include faceted semantic search and browsing engines for 1) statutes and 2) court decisions, as well as 3) a service for finding court decisions similar to a given one. A novelty of LAWSAMPO is the provision of ready-to-use tooling for exploring and analyzing legal documents, based on the "Sampo" model.
This paper presents an automatic annotation tool AATOS for providing documents with semantic annotations. The tool links entities found from the texts to ontologies defined by the user. The application is highly configurable and can be used with different natural language Finnish texts. The application was developed as a part of the WarSampo 1 and Semantic Finlex 2 projects and tested using Kansa Taisteli magazine articles and consolidated Finnish legislation of Semantic Finlex. The quality of the automatic annotation was evaluated by measuring precision and recall against existing manual annotations. The results showed that the quality of the input text, as well as the selection and configuration of the ontologies impacted the results.
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