The L eibniz L ist as Linguistic Linked Data in the L i L a Knowledge Base (2025)

Abstract: This paper presents the integration of the Leibniz List, a concept list from the Concepticon project, into the LiLa Knowledge Base of Latin interoperable resources. The modeling experiment was conducted using W3C standards like Ontolex and SKOS. This work, which originated in a project for a university course, is limited to a short list of words, but it already enables interoperability between the Concepticon and the language resources in a LOD architecture like LiLa. The integration enriches the LiLa ecosystem, allowing users to explore Latin lexicon from an onomasiological perspective and links concepts to lexical entries from various dictionaries and corpus attestations. The work showcases how standard Semantic Web technologies can effectively model and connect historical concept lists within larger linguistic knowledge infrastructures and provides an example for further experiments with the Concepticon’s data.

## introduction the aim of the present study is to model one concept list from the concepticon project (list et al., 2016) foot_0 as linguistic linked open data (llod) and to connect it to the knowledge base (kb) of linguistic resources for latin made available by the lila linking latin project. @xcite specifically, the study focuses on the concepts included in a list compiled by the philosopher g. w. leibniz and now published in the concepticon. the paper discusses how the latin verbalizations of these concepts were linked to the lemmas of the lila lemma bank with the help of two widely used ontologies such as skos and the ontolex-lemon model. our work leverages the lemma-as-gateway approach promoted by lila to make leibniz's concepts part of a network of interoperable linguistic resources; at the same time, it integrates the concept-based perspective of the concepticon into the lila ecosystem for the first time. the introduction of a concept list from this project allows us to widen the range and type of lexical resources available in lila and enables researchers interested in an onomasiological approach to lexicon (from the concepts to the words used to express them) to make use of the network of data in the kb. while the concept list described here is quite small, the work is a first step in modeling and integrating a similar resource. the paper is organized as follows. sections 1.1 and 1.2 introduce the concepticon and the leibniz list respectively. section 1.3 provides a short overview of lila. section 2 describes the work undertaken to model the data and the final results. section 3 summarizes the conclusions and future perspectives. ## modelling the concepticon's leibniz list in this section, we explore how we translated leibniz's latin lexicalizations of his concepts by relying on the same model that is used by lila, and how we linked this information to the lemma bank. moreover, we show that once the lexicalization of @xcite see http://lila-erc.eu/ontologies/lila/lemma . a concept is modeled as lod, it becomes easy to integrate much of the information provided by the concepticon using a popular w3c standard, namely the simple knowledge organization system (skos). @xcite the lexical information provided in the leibniz list is readily expressed with the ontolex-lemon model. intuitively, the concepts collected by leibniz (like all concepts mapped by the concepticon, which point to notions and ideas not organized into formal ontologies) are perfect examples of instances of the class "lexical concept" in ontolex. @xcite while the concepticon dataset only provides labels for them, a full lexicalization via ontolex enables lexicographers to extend the range of possible linguistic metadata that can be attached to the words and, especially, to connect those words to a wealth of additional linguistic information. note that, as the lists in the concepticon start from concepts, generally (and effectively with the leibniz list) ambiguity and polysemy do not pose a problem: each concept in the list is verbalized by a single lexical entry. if multiple lists use the same word to verbalize different concepts (e.g. "river bank" and "financial institution" with en. bank), curators will have to choose whether to create one single lexical entry with multiple senses, or multiple entries with a different form of mapping provided between them. anyway, this case did not occur in our work. to generate rdf representations of the lexical entries, lexical concepts and senses, we started from the tsv file downloaded from the concepticon project and we modeled it using the software openrefine and a dedicated rdf plugin. @xcite with such a limited list, the mapping to the lila lemmas was conducted manually, relying on the lila's lemma query interface (passarotti et al., 2024). for the lexical entries and senses (which in ontolex reify the relation between words and concepts) we defined custom uris within the lila namespace. @xcite to collect all lexical entries connected to the list, we also created a lexicon using the ontolex' lime model for lexicons and metadata. @xcite for the concepts and concept lists, on the 11 https://www.w3.org/2004/02/skos/ . @xcite see the documentation at https://www.w3.org/2016/ 05/ontolex/#lexical-concept . as said, the concepticon aligns all the different concept lists into concept sets. once again, the nature of these notions is not difficult to capture using standard vocabularies of the semantic web. the properties and classes defined in skos can be leveraged to express the mapping and the simple organization (which includes broad/narrow, or "see also" relations) provided by the project. the class of skos:concept is both intuitively and factually appropriate to represent the entries in the concept lists; glosses and definitions such as those found in the concepticon are recorded via the skos:definition property. each list represents an informal and historically independent collection of (skos) concepts, which is compatible with the definition of a skos:conceptscheme (allemang et al., 312). the nature of concept sets is, on the other hand, less intuitive. while it would be possible to capture its specific essence by developing a dedicated concepticon ontology, we preferred not to take this approach and rather rely on the available w3c standards only. from this perspective, the essential goal that concept sets are pursuing, i.e. the mapping of concepts from independent lists, can be readily captured in skos. in this perspective, concept sets are also instances of the skos:concept class, not belonging to concept lists, but assigned to a dedicated concepticon skos:conceptscheme. the