This paper describes three online services designed to ease the tasks of querying and populating the linguistic resources for Latin made interoperable through their publication as Linked Open Data in the LiLa Knowledge Base. As for querying the KB, we present an interface to search the collection of lemmas that represents the core of the Knowledge Base, and an interactive, graphical platform to run queries on the resources currently interlinked. As for populating the KB with new textual resources, we describe a tool that performs automatic tokenization, lemmatization and Part-of-Speech tagging of a raw text in Latin and links its tokens to LiLa.

The large availability of processable textual resources for Classical Latin has made it possible to study Latin literature through methods and tools that support distant reading. This paper describes a number of experiments carried out to test the possibility of investigating the thematic distribution of the Classical Latin corpus Opera Latina by means of topic modeling. For this purpose, we train, optimize and compare two neural models, Product-of-Experts LDA (ProdLDA) and Embedded Topic Model (ETM), opportunely revised to deal with the textual data from a Classical Latin corpus, to evaluate which one performs better both on the basis of topic diversity and topic coherence metrics, and from a human judgment point of view. Our results show that the topics extracted by neural models are coherent and interpretable and that they are significant from the perspective of a Latin scholar. The source code of the proposed model is available at https://github.com/MIND-Lab/LatinProdLDA.

This paper describes the steps undertaken to include data from Antonio Velez’s bilingual Latin-Portuguese dictionary (Index Totius Artis, 1744) into the LiLa Knowledge Base of interoperable linguistic resources for Latin. The paper focuses on how the lexical and lexicographic information of the source dictionary was modelled by using respectively the Lexicon Model for Ontologies (OntoLex-lemon) and its lexicog module. The linking process of the dictionary entries with those of the LiLa collection of Latin lemmas is detailed, discussing issues in dealing with ambiguities and typographical errors found in the source. The result is the first Latin-Portuguese lexical resource made interoperable with the (meta)data of the other linguistic resources for Latin interlinked in the LiLa Knowledge Base, providing new ways of assessing the dictionary information or using its content as starting point to explore the connections with other interlinked linguistic resources. A couple of use case scenarios illustrate those possibilities.

This paper describes the process of interlinking the 130 Classical Latin texts provided by an annotated corpus developed at the LASLA laboratory with the LiLa Knowledge Base, which makes linguistic resources for Latin interoperable by following the principles of the Linked Data paradigm and making reference to classes and properties of widely adopted ontologies to model the relevant information. After introducing the overall architecture of the LiLa Knowledge Base and the LASLA corpus, the paper details the phases of the process of linking the corpus with the collection of lemmas of LiLa and presents a federated query to exemplify the added value of interoperability of LASLA’s texts with other resources for Latin.

Although the Universal Dependencies initiative today allows for cross-linguistically consistent annotation of morphology and syntax in treebanks for several languages, syntactically annotated corpora are not yet interoperable with many lexical resources that describe properties of the words that occur therein. In order to cope with such limitation, we propose to adopt the principles of the Linguistic Linked Open Data community, to describe and publish dependency treebanks as LLOD. In particular, this paper illustrates the approach pursued in the LiLa Knowledge Base, which enables interoperability between corpora and lexical resources for Latin, to publish as Linguistic Linked Open Data the annotation layers of two versions of a Medieval Latin treebank (the Index Thomisticus Treebank).

In this paper we describe the process of inclusion of etymological information in a knowledge base of interoperable Latin linguistic resources developed in the context of the LiLa: Linking Latin project. Interoperability is obtained by applying the Linked Open Data principles. Particularly, an extensive collection of Latin lemmas is used to link the (distributed) resources. For the etymology, we rely on the Ontolex-lemon ontology and the lemonEty extension to model the information, while the source data are taken from a recent etymological dictionary of Latin. As a result, the collection of lemmas LiLa is built around now includes 1,465 Proto-Italic and 1,393 Proto-Indo-European reconstructed forms that are used to explain the history of 1,400 Latin words. We discuss the motivation, methodology and modeling strategies of the work, as well as its possible applications and potential future developments.

The interoperability between lemmatized corpora of Latin and other resources that use the lemma as indexing key is hampered by the multiple lemmatization strategies that different projects adopt. In this paper we discuss how we tackle the challenges raised by harmonizing different lemmatization criteria in the context of a project that aims to connect linguistic resources for Latin using the Linked Data paradigm. The paper introduces the architecture supporting an open-ended, lemma-based Knowledge Base, built to make textual and lexical resources for Latin interoperable. Particularly, the paper describes the inclusion into the Knowledge Base of its lexical basis, of a word formation lexicon and of a lemmatized and syntactically annotated corpus.

Although lexicography of Latin has a long tradition dating back to ancient grammarians, and almost all Latin grammars devote to wordformation at least one part of the section(s) concerning morphology, none of the today available lexical resources and NLP tools of Latin feature a wordformation-based organization of the Latin lexicon. In this paper, we describe the first steps towards the semi-automatic development of a wordformation-based lexicon of Latin, by detailing several problems occurring while building the lexicon and presenting our solutions. Developing a wordformation-based lexicon of Latin is nowadays of outmost importance, as the last years have seen a large growth of annotated corpora of Latin texts of different eras. While these corpora include lemmatization, morphological tagging and syntactic analysis, none of them features segmentation of the word forms and wordformation relations between the lexemes. This restricts the browsing and the exploitation of the annotated data for linguistic research and NLP tasks, such as information retrieval and heuristics in PoS tagging of unknown words.