Annotation of Toponyms in TEI Digital Literary Editions and Linking to the Web of Data

International audienceThis paper aims to discuss the challenges and benefits of the annotation of place names in literary texts and literary criticism. We shall first highlight the problems of encoding spatial information in digital editions using the TEI format by means of two manual annotation experiments and the discussion of various cases. This will lead to the question of how to use existing semantic web resources to complement and enrich toponym markup , in particular to provide mentions with precise geo-referencing. Finally the automatic annotation of a large corpus will show the potential of visualizing places from texts, by illustrating an analysis of the evolution of literary life from the spatial and geographical point of view.Este artigo aborda as dificuldades e as vantagens da anotação dos nomes de lugar em textos literários e de crítica literária. Começamos por realçar os problemas de codifi-cação da informação espacial em edições digitais usando o formato TEI, através de duas experiências de anotação manual e da análise de diversos casos. Isto conduzirá à questão de como utilizar os recursos da web semântica para complementar e enrique-cer a marcação de topónimos, em particular com georreferenciação rigorosa. Por último, a anotação automática de um grande corpus irá mostrar o potencial de visuali-zação de locais a partir de textos, ilustrando a análise da evolução da vida literária segundo um ponto de vista espacial e geográfico. Palavras-chave: estudos literários digitais; topónimos; web semântica; bases de dados geográficas; mapas e visualizações

Flabase: towards the creation of a flamenco music knowledge base

Online information about flamenco music is scattered overdifferent sites and knowledge bases. Unfortunately, thereis no common repository that indexes all these data. Inthis work, information related to flamenco music is gath-ered from general knowledge bases (e.g., Wikipedia, DB-pedia), music encyclopedias (e.g., MusicBrainz), and spe-cialized flamenco websites, and is then integrated into anew knowledge base called FlaBase. As resources fromdifferent data sources do not share common identifiers, aprocess of pair-wise entity resolution has been performed.FlaBase contains information about 1,174 artists, 76pa-los(flamenco genres), 2,913 albums, 14,078 tracks, and771 Andalusian locations. It is freely available in RDF andJSON formats. In addition, a method for entity recognitionand disambiguation for FlaBase has been created. The sys-tem can recognize and disambiguate FlaBase entity refer-ences in Spanish texts with an f-measure value of 0.77. Weapplied it to biographical texts present in Flabase. By usingthe extracted information, the knowledge base is populatedwith relevant information and a semantic graph is createdconnecting the entities of FlaBase. Artists relevance is thencomputed over the graph and evaluated according to a fla-menco expert criteria. Accuracy of results shows a highdegree of quality and completeness of the knowledge base

Event-based Access to Historical Italian War Memoirs

The progressive digitization of historical archives provides new, often domain specific, textual resources that report on facts and events which have happened in the past; among these, memoirs are a very common type of primary source. In this paper, we present an approach for extracting information from Italian historical war memoirs and turning it into structured knowledge. This is based on the semantic notions of events, participants and roles. We evaluate quantitatively each of the key-steps of our approach and provide a graph-based representation of the extracted knowledge, which allows to move between a Close and a Distant Reading of the collection.Comment: 23 pages, 6 figure

Domain-specific named entity disambiguation in historical memoirs

This paper presents the results of the extraction of named entities from a collection of historical memoirs about the italian Resistance during the World War II. The methodology followed for the extraction and disambiguation task will be discussed, as well as its evaluation. For the semantic annotations of the dataset, we have developed a pipeline based on established practices for extracting and disambiguating Named Entities. This has been necessary, considering the poor performances of out-of-the-box Named Entity Recognition and Disambiguation (NERD) tools tested in the initial phase of this work.Questo articolo presenta l’attività di estrazione di entità nominate realizzata su una collezione di memorie relative al periodo della Resistenza italiana nella Seconda Guerra Mondiale. Verrà discussa la metodologia sviluppata per il processo di estrazione e disambiguazione delle entità nominate, nonché la sua valutazione. L’implementazione di una metodologia di estrazione e disambiguazione basata su lookup si è resa necessaria in considerazione delle scarse prestazioni dei sistemi di Named Entity Recognition and Disambiguation (NERD), come si evince dalla discussione nella prima parte di questo lavoro

A knowledge-based approach to information extraction for semantic interoperability in the archaeology domain

The paper 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. Performance is evaluated via the Gold Standard method. 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 (ISO 21127:2006) CIDOC Conceptual Reference Model (CRM) for cultural heritage and its archaeological extension, CRM-EH, together with concepts from English Heritage thesauri and glossaries.Relation Extraction performance benefits from a syntactic based definition of relation extraction patterns derived from domain oriented corpus analysis. The evaluation also shows clear benefit in the use of assistive 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 relation extraction rules for the recognition of semantic relationships from phrases of unstructured text. The semantic annotations have proven capable of supporting semantic query, document study and cross-searching via the ontology framework

Knowledge Extraction for Art History: the Case of Vasari’s The Lives of The Artists (1568)

Knowledge Extraction (KE) techniques are used to convert unstructured information present in texts to Knowledge Graphs (KGs) which can be queried and explored. Despite their potential for cultural heritage domains, such as Art History, these techniques often encounter limitations if applied to domain-specific data. In this paper we present the main challenges that KE has to face on art-historical texts, by using as case study Giorgio Vasari’s The Lives of The Artists. This paper discusses the following NLP tasks for art-historical texts, namely entity recognition and linking, coreference resolution, time extraction, motif extraction and artwork extraction. Several strategies to annotate art-historical data for these tasks and evaluate NLP models are also proposed

Knowledge Extraction for Art History: the Case of Vasari’s The Lives of The Artists (1568)

Knowledge Extraction (KE) techniques are used to convert unstructured information present in texts to Knowledge Graphs (KGs) which can be queried and explored. Despite their potential for cultural heritage domains, such as Art History, these techniques often encounter limitations if applied to domain-specific data. In this paper we present the main challenges that KE has to face on art-historical texts, by using as case study Giorgio Vasari's The Lives of The Artists. This paper discusses the following NLP tasks for art-historical texts, namely entity recognition and linking, coreference resolution, time extraction, motif extraction and artwork extraction. Several strategies to annotate art-historical data for these tasks and evaluate NLP models are also proposed