Interlinking through Lemmas. Linking Linguistic Resources to a lexically-based LLOD Knowledge Base

1. Objectives

The tutorial aims to introduce the architecture, use and enhancement of the LiLa Knowledge Base of interlinked linguistic resources for Latin, developed in the context of the LiLa: Linking Latin project. In particular, the tutorial will present how the Linked-Data model adopted by LiLa is used to connect distributed lexical and textual resources, to ensure their interoperability. We show how, via lemmatisation, texts become part of this network of resources. We provide participants with a theoretical introduction to the architecture of LiLa, as well as hands-on support in their interaction with the LiLa Knowledge Base.

The proposed tutorial falls within the field of Linguistic Linked Open Data (LLOD: Cimiano et al. 2020). While we focus on Latin, the methods discussed are language independent and thus have a much wider application, proving useful for similar initiatives on other languages.

Starting from the experience of LiLa, we introduce the audience to some of the most relevant topics in current digital textual studies and linguistic resources, including:

• Language (Meta)data. Tools and techniques of linguistic annotation. Specific concepts and technologies discussed: tokenisation, part-of-speech tagging, lemmatisation, and application of a Natural Language Processing (NLP) pipeline (UDPipe) with specific models trained on a large Latin corpus.
• Knowledge Graphs. Tools and techniques to interoperably link linguistically-annotated datasets. Specific concepts and technologies discussed: interoperability standards, ontologies, RDF, SPARQL, Linguistic Linked Data.
• Use Cases in Language, Data and Knowledge. Possible uses for philology and linguistics, namely searches combining etymology, polarity, frequency, (graphical) variation, meaning, and more.

2. Detailed description

We propose a 1-day tutorial, divided in two sections.

3. Instructors

Presenters and assistants (all affiliated with Università Cattolica del Sacro Cuore):

• Marco Passarotti (marco.passarotti@unicatt.it). Associate Professor of Computational Linguistics and Director of the CIRCSE Research Centre. Since 2006 he has headed the Index Thomisticus Treebank project. He is the Principal Investigator of the LiLa: Linking Latin ERC Consolidator Grant (2018–2023).
• Flavio Massimiliano Cecchini (flavio.cecchini@unicatt.it) graduated in Mathematics from the Università degli Studi in Milan and then focused his interest towards NLP and Computational Linguistics; he obtained a PhD in Computer Science with a thesis about Word Sense Discrimination. Currently, Flavio works as a postdoctoral researcher on the LiLa: Linking Latin project.
• Francesco Mambrini (francesco.mambrini@unicatt.it). PhD in Classical Philology (University of Trento / EHESS). Researcher for the LiLa: Linking Latin project. Previously, he worked at the Deutsches Archäologisches Institut, Berlin, and at the University of Leipzig. His research interests focus on the language and style of Ancient Greek and Latin literary texts.

Assistants:

• Eleonora Litta (EleonoraMaria.Litta@unicatt.it). Eleonora has worked on the development of digital language resources, text analysis, corpus and computational linguistics. She was awarded a Marie Skłodowska-Curie Research fellowship to develop WFL, a word formation lexicon for Latin, at the Università Cattolica del Sacro Cuore. She is currently working as part of the LiLa project on a new Latin valency lexicon and WordNet.
• Giovanni Moretti (giovanni.moretti@unicatt.it). Software developer. Since 2007 Giovanni has been working in many Human Language Technology projects developing scripts and web interfaces for data acquisition, annotation, analysis and data visualisation. Currently, he is working in the LiLa: Liking Latin project strengthening his expertise in Linked Data technology.
• Matteo Pellegrini (matteo.pellegrini@unicatt.it). Postdoctoral researcher working on the LiLa: Linking Latin project. His research is mainly focused on inflectional morphology, with a specific interest in automatic processing of Latin morphology.
• Paolo Ruffolo (paolo.ruffolo@posteo.eu). Computer science engineer. Worked as software developer and tester, database designer and administrator, and data analyst both for research institutions and private companies. Currently working on the LiLa: Liking Latin project.
• Rachele Sprugnoli (rachele.sprugnoli@unicatt.it). Postdoctoral researcher working on the LiLa: Linking Latin project. Her research is mainly focused on text annotation, evaluation of NLP tools and on how computational methods and text analysis technologies can be applied to the treatment of cultural content.

4. Target audience and expected attendance

This tutorial is intended for those who wish to explore solutions to publish texts using LOD. Although we focus on our experience with Latin, we welcome any participant interested in the theme of textual resources and LOD; prior knowledge of Latin and/or LOD is not required.

We expect around 20-30 participants from different backgrounds: computational linguists, theoretical linguists, classicists, philologists.

5. Proposed budget

As the tutorial will be run by the members of the LiLa team, no costs to pay for the instructors is foreseen.

Neither publication of proceedings nor invitation of keynote speakers is planned. The website of the tutorial (if required to be external to that of EADH 2021) will be hosted on that of LiLa, free of charge.

Should the tutorial take place in loco, the costs for the coffee breaks will be covered by the tutorial fees.

6. Requirements and format

Should the tutorial take place in loco, we would require a projector and a whiteboard with markers.

Should it take place online, we would adopt Zoom as our preferred platform for its “Breakout Rooms” functionality.