Natural Language Processing for Ancient Greek
Design, advantages and challenges of language models
Bibliographic Data
| ID | 20344892 |
|---|---|
| Authors | Silvia Stopponi (0000-0002-3041-3477, University of Groningen), Nilo Pedrazzini (0000-0003-3757-2961, The Alan Turing Institute), Saskia Peels‐Matthey (University of Groningen), Saskia Peels-Matthey (University of Groningen), Barbara Mcgillivray (0000-0003-3426-8200, King's College London), Malvina Nissim (0000-0001-5289-0971, University of Groningen) |
| Year | 2024 |
| Volume | 41 |
| Issue | 3 |
| Pages | 414-435 |
| Publication date | 2024-10-22 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Diachronica (JOURNAL) |
| Journal identifiers | ISSN: 0176-4225 • E-ISSN: 1569-9714 |
| Publisher | John Benjamins Publishing Company (PUBLISHER • NL) |
| DOI | 10.1075/dia.23013.sto |
| OpenAlex | W4400238864 |
| Language | EN |
| References cited | 22 |
Computational methods have produced meaningful and usable results to study word semantics, including semantic change. These methods, belonging to the field of Natural Language Processing, have recently been applied to ancient languages; in particular, language modelling has been applied to Ancient Greek, the language on which we focus. In this contribution we explain how vector representations can be computed from word co-occurrences in a corpus and can be used to locate words in a semantic space, and what kind of semantic information can be extracted from language models. We compare three different kinds of language models that can be used to study Ancient Greek semantics: a count-based model, a word embedding model and a syntactic embedding model; and we show examples of how the quality of their representations can be assessed. We highlight the advantages and potential of these methods, especially for the study of semantic change, together with their limitations
Distributional semantics · Embedding · Linguistics · Natural language · Natural language processing · Programming language · Semantic compression · Semantic computing · Semantic similarity · Semantic technology · Semantic Web · USable · Word embedding · World Wide Web · Computer Science · Language and cultural evolution · Natural Language Processing Techniques · Topic Modeling · Artificial Intelligence
| Citation velocity | historical |
|---|---|
| Highly cited | No |