Livio Robaldo

Welcome to the homepage of Livio Robaldo. I am a Senior Lecturer in LegalTech working at the Legal Innovation Lab Wales of Swansea University. I earned a Ph.D. in Computer Science at the University of Turin in 2007; after my PhD, I worked until 2015 at the University of Turin on various research projects in Natural Language Semantics (NLS) and Natural Language Processing (NLP). From 2015 to 2020, I worked at the University of Luxembourg on LegalTech research projects applying my past results in NLS and NLP to legal texts. In 2020, I got a Senior Lecturer position at Swansea University.

My full Curriculum Vitae is available here, while the shorter Europass CV version is available here.

The LegalTech projects in which I work/worked are described below. Past research interests include Natural Language Quantifiers, semantics of Discourse Connectives, Dependency Parsing, Sentiment Analysis, and Gamification-based approaches to corpora building.

Projects in LegalTech

LegalTech for Cybersecurity (Aug 2022 - Aug 2023)

The project is sponsored by the Morgan Advanced Studies Institute of Swansea University and it is intended to support networking activities with Old Dominion University (Virginia, US) with the aim of researching novel methods to apply LegalTech technologies for cybersecurity, while taking into account legal and financial perspectives in the insurance domain. The activity aims at preparing and submitting further interdisciplinary research project proposals in the field. I am the principal investigator of the project, which also involves other seven professors in IT, Law, and Economics from the two universities.

LAST-JD RIoE (Nov 2019 - Oct 2023)

LAST-JD RIoE (LAST-JD - Rights of the Internet of Everything) is supported by a Marie Skłodowska-Curie Innovative Training Networks . It has been retained for funding with an overall score of 94.8%. My involved in LAST-JD started in 2014 at the University of Turin. From 2015 until 2020, I was responsible of LAST-JD for the University of Luxembourg. I followed the administrative activities of the school, e.g. participating to the doctoral boards, giving classes to introduce NLP for the legal domain to the students, following and advising them in their research activity, etc.

DAPRECO (Feb 2017 - Jun 2019)

DAPRECO (DAta Protection REgulation COmpliance) was a CORE project that has been retained for funding on Nov 2016. DAPRECO is the single senior CORE project proposed by SnT in 2016 that has been retained for funding, out of 18 submitted ones. The project was designed as a use case of my past project ProLeMAS and it led to the DAPRECO knowledge base [Robaldo et al., 2020], which represents the norms from the General Data Protection Regulation (GDPR) in reified I/O logic [Robaldo and Sun, 2017] by using the concepts from the Privacy Ontology (PrOnto) [Palmirani et al., 2018a].

MIREL (Jan 2016 - Dec 2019)

MIREL (MIning and REasoning on Legal texts) is supported by a Marie Skłodowska-Curie Research and Innovation Staff Exchange project . It has been retained for funding with an overall score of 97.2%. I coordinated the writing of MIREL and I managed its activities for all over the duration of the project, as certified in this statement. MIREL promoted mobility and staff exchange among the 16 international partners, to create an inter-disciplinary consortium in Law and Artificial Intelligence areas including NLP, Computational Ontologies, Argumentation, Logic&Reasoning, and Business Process Management.

ProLeMAS (Jun 2015 - May 2017)

ProLeMAS (PROcessing LEgal language in normative Multi-Agent Systems) was supported by a Marie Skłodowska-Curie Individual fellowship . It has been retained for funding with an overall score of 96.4%. ProLeMAS aimed at (1) using reification to fill the gap between the current formalizations in deontic logics and the richness of natural language semantics and (2) implementing tools for (semi-)automatically building machine-readable representations from legal texts via NLP. In the context of ProLeMAS, I visited for six months the private company APIS Hristovich EOOD.

EUCases (Oct 2013 - Oct 2015)

EUCases (Linking Legal Open Data in Europe) was a collaborative Research Project supported by the Seventh Framework Programme (FP7) funding and involving five partners, among which Nomotika S.R.L. and APIS Hristovich EOOD. The project EUCases was my first relevant experience in LegalTech. I was responsible of the NLP tasks for the Italian language, as certified in this statement. The project ProLeMAS was built on EUCases results. Nomotika S.R.L. and APIS Hristovich EOOD, were subsequently involved in the projects ProLeMAS, MIREL, and LAST-JD RoIE.

ICT4LAW (Mar 2009 - Feb 2012)

ICT4LAW was a large interdisciplinary research project involving twelve partners, six academics and six industrials. The goal was to create novel services for citizens, enterprises, public administration and policy makers. My role in the project was minimal, but it was useful to learn general expertise in LegalTech. I developed rule-bases systems for recognizing modificatory provisions and I carried out dependency parsing to feed statistical classifiers. The ICT4LAW project led to the creation of the spin-off Nomotika S.R.L., founded by the University of Turin and Augeos S.P.A..

Past research

NL Quantifiers

In the context of my PhD thesis, I worked on formal representation of NL quantifiers. In particular, I devised a new logical framework to properly represent Scopeless readings, such as cumulative and collective readings. I authored six journal publications and several conference/workshop ones on the topic and I am the single author of four of these journal publications. My last publication on the topic was (Robaldo, Szymanik, Meijering, 2014), which are coauthored with Jakub Szymanik and Ben Meijering. After that publication, I stopped working on NL Quantifiers. On the other hand, Jakub was later awarded by an ERC Starting Grant on related topics (developing cognitive semantics of generalized quantifiers). Congrats Jakub!

Penn Discourse Treebank (PDTB)

The PDTB is a corpus developed at the University of Pennsylvania (UPenn). The PDTB is, to date, the largest annotation effort at the discourse level, providing annotations of the argument structure, attribution and semantics of discourse connectives. After my PhD thesis, I visited University of Pennsylvania for five months (and later again in 2009 for two months) where I started working with the PDTB research group. I contributed to the writing of the PDTB 2.0 annotation manual and the sense annotation in the release 2.0 of the corpus. During that period, I also started working with reification-based semantics, specifically the approach of Jerry R. Hobbs, and I used it to model concessive relations found in the PDTB.

Sentiment Analysis

In 2013, I defined, together with Luigi Di Caro, an XML formalism called OpinionMining-ML for tagging users' opinions on products and services, and I built a corpus of 1000 comments about restaurants taken from www.2spaghi.it, one of the biggest web2.0 sites about Italian restaurants and pizzerias. Afterwards, I won the Working Capital Accelerator 2014, a Telecom Italia grant to support new startups and innovative research projects, with the project SentiTagger, aiming at automatically tagging comments in OpinionMining-ML. The selection was highly competitive: only 40 projects out of about 1,300 submitted ones were selected. Each selected project was granted 25,000 euros from Telecom Italia.

Gamification

In 2013, I worked on Gamification-based approaches to corpora building, pionereed by Massimo Poesio. I was specifically involved in the Phrase Detective game-with-a-purpose, aiming at creating anaphorically annotated resources through Web cooperation. I was an expert annotator of the game and I developed a converter from Italian texts to the input format of the game via dependency parsing, in order to allow annotations in Italian. Massimo Poesio was later awarded with an ERC Advanced grant, on the project ''DALI - Disagreements and Language Interpretation'', which proposes more advanced games, drawn from Phrase Detective, to collect massive amounts of data about anaphora from people playing them. Congrats Massimo!