<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Lexicography | Michele Ciletti - Personal Website</title><link>https://mikcil.github.io/tags/lexicography/</link><atom:link href="https://mikcil.github.io/tags/lexicography/index.xml" rel="self" type="application/rss+xml"/><description>Lexicography</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 17 Jun 2026 00:00:00 +0000</lastBuildDate><image><url>https://mikcil.github.io/media/icon_hu_ddb90028b3b04059.png</url><title>Lexicography</title><link>https://mikcil.github.io/tags/lexicography/</link></image><item><title>Open-vocabulary Word Sense Disambiguation at Digital Latin III</title><link>https://mikcil.github.io/post/digital-latin-iii/</link><pubDate>Wed, 17 Jun 2026 00:00:00 +0000</pubDate><guid>https://mikcil.github.io/post/digital-latin-iii/</guid><description>&lt;p>I had a wonderful experience at Digital Latin III, the workshop on digital tools and AI for research on the Latin lexicon organised by the University of Siena (15-16 June 2026)! It was a truly innovative conference and an amazing scientific environment: the program went from medieval glossaries and the digital edition of the &lt;em>Dictionary of Medieval Latin from British Sources&lt;/em> to transformer models trained on Latin.&lt;/p>
&lt;p>I presented some preliminary findings on open-vocabulary, LLM-based Word Sense Disambiguation, aimed mainly (but not only) at historical languages. Most WSD systems choose a sense from a list of candidates that a lexical resource already provides for the target word; for Latin, that list is often incomplete or missing altogether. The pipeline I presented, Inspicio, does without it. An LLM translates the Latin sentence into English twice, once literally and once more naturally, and then proposes English substitute lemmas and dictionary-style definitions for the target word. These are used to search all the verb synsets of the Open English WordNet, combining dense similarity between definitions and synsets with sparse matching on the lemmas. Synsets found by both methods get a boost, and a final Maximal Marginal Relevance step makes sure that near-duplicate WordNet senses do not push genuinely different interpretations out of the ranking.&lt;/p>
&lt;p>On Latin perception verbs and a selection of sentences from LatinISE, the best combination of LLM and embedding model reached 90% Recall@20. These are still early numbers. The next steps are adding an LLM reranker, testing smaller open-weight models, going beyond verbs, and trying the same approach on other historical languages.&lt;/p>
&lt;p>The code is
. Check out the
too: the proceedings are coming soon!&lt;/p>
&lt;p>
&lt;figure id="figure-presenting-the-retrieval-step-of-the-pipeline">
&lt;div class="flex justify-center ">
&lt;div class="w-full" >
&lt;img alt="Presenting the merge and diversify step of the pipeline on Google Meet"
srcset="https://mikcil.github.io/post/digital-latin-iii/remote-talk_hu_5f868773b43700e3.webp 320w, https://mikcil.github.io/post/digital-latin-iii/remote-talk_hu_86f07121170752ab.webp 480w, https://mikcil.github.io/post/digital-latin-iii/remote-talk_hu_c9fac2a74fbcd68c.webp 760w"
sizes="(max-width: 480px) 100vw, (max-width: 768px) 90vw, (max-width: 1024px) 80vw, 760px"
src="https://mikcil.github.io/post/digital-latin-iii/remote-talk_hu_5f868773b43700e3.webp"
width="760"
height="428"
loading="lazy" data-zoomable />&lt;/div>
&lt;/div>&lt;figcaption>
Presenting the retrieval step of the pipeline
&lt;/figcaption>&lt;/figure>
&lt;/p></description></item><item><title>LLM-Driven, Open-Vocabulary Word Sense Disambiguation for Latin Digital Lexicography</title><link>https://mikcil.github.io/event/digital-latin-iii/</link><pubDate>Tue, 16 Jun 2026 12:10:00 +0000</pubDate><guid>https://mikcil.github.io/event/digital-latin-iii/</guid><description>&lt;p>My talk was part of the second day of the workshop, &amp;ldquo;Intelligenza artificiale e lingua latina&amp;rdquo;. The workshop was organised by the Centro di Studi Comparati I Deug-Su and the Department of Philology and Criticism of Ancient and Modern Literatures of the University of Siena.&lt;/p>
&lt;p>I presented an early version of Inspicio, the pipeline later described in my
. The code is
, and the proceedings of the workshop are in preparation.&lt;/p>
&lt;p>I also wrote a
about the workshop.&lt;/p></description></item></channel></rss>