Abstract
The Index Thomisticus Treebank is the largest available treebank for Latin; it contains Medieval Latin texts by Thomas Aquinas.
After experimenting on its data with a number of dependency parsers based on different supervised machine learning techniques,
we found that DeSR with a multilayer perceptron algorithm, a right-to-left transition, and a tailor-made feature model is the parser
providing the highest accuracy rates. We improved the results further by using a technique that combines the output parses of DeSR
with those provided by other parsers, outperforming the previous state of the art in parsing the Index Thomisticus Treebank. The
key idea behind such improvement is to ensure a sufficient diversity and accuracy of the outputs to be combined; for this reason, we
performed an in-depth evaluation of the results provided by the different parsers that we combined. Finally, we assessed that, although
the general architecture of the parser is portable to Classical Latin, yet the model trained on Medieval Latin is inadequate for such purpose.
Lingua originale | English |
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Titolo della pubblicazione ospite | Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) |
Pagine | 683-688 |
Numero di pagine | 6 |
Stato di pubblicazione | Pubblicato - 2016 |
Evento | Tenth International Conference on Language Resources and Evaluation (LREC 2016) - Portorož Durata: 23 mag 2016 → 28 mag 2016 |
Convegno
Convegno | Tenth International Conference on Language Resources and Evaluation (LREC 2016) |
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Città | Portorož |
Periodo | 23/5/16 → 28/5/16 |
Keywords
- Latin
- Parsing