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New LLM pipeline retrieves word senses for historical languages

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new pipeline called Inspicio that uses LLMs to retrieve senses for words in historical languages without needing a pre-existing sense inventory. This method generates English translations and definitions for context, then uses a hybrid retrieval system combining similarity, lemma matching, and re-ranking. Evaluations on Latin, Ancient Greek, and Italian demonstrated high recall rates, with each component of the pipeline contributing to its effectiveness. AI

IMPACT Enables deeper linguistic analysis of historical texts by overcoming limitations of traditional word sense disambiguation methods.

RANK_REASON The cluster contains an academic paper detailing a new method for word sense disambiguation in historical languages. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New LLM pipeline retrieves word senses for historical languages

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The cluster contains an academic paper detailing a new method for word sense disambiguation in historical languages. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Michele Ciletti ·

    Inspicio: Open-Vocabulary, LLM-Based Sense Retrieval for Historical Languages

    arXiv:2609.00998v1 Announce Type: cross Abstract: Word Sense Disambiguation has advanced rapidly for English and a handful of well-resourced modern languages, but it continues to assume the existence of a sense inventory and a word-to-sense mapping in the source language (Navigli…

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