The Royal Society Corpus: From Uncharted Data to Corpus

Hannah Kermes, Stefania Degaetano-Ortlieb, Ashraf Khamis, Jörg Knappen, Elke Teich


Abstract
We present the Royal Society Corpus (RSC) built from the Philosophical Transactions and Proceedings of the Royal Society of London. At present, the corpus contains articles from the first two centuries of the journal (1665―1869) and amounts to around 35 million tokens. The motivation for building the RSC is to investigate the diachronic linguistic development of scientific English. Specifically, we assume that due to specialization, linguistic encodings become more compact over time (Halliday, 1988; Halliday and Martin, 1993), thus creating a specific discourse type characterized by high information density that is functional for expert communication. When building corpora from uncharted material, typically not all relevant meta-data (e.g. author, time, genre) or linguistic data (e.g. sentence/word boundaries, words, parts of speech) is readily available. We present an approach to obtain good quality meta-data and base text data adopting the concept of Agile Software Development.
Anthology ID:
L16-1305
Volume:
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:
May
Year:
2016
Address:
Portorož, Slovenia
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1928–1931
Language:
URL:
https://aclanthology.org/L16-1305
DOI:
Bibkey:
Cite (ACL):
Hannah Kermes, Stefania Degaetano-Ortlieb, Ashraf Khamis, Jörg Knappen, and Elke Teich. 2016. The Royal Society Corpus: From Uncharted Data to Corpus. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1928–1931, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):
The Royal Society Corpus: From Uncharted Data to Corpus (Kermes et al., LREC 2016)
Copy Citation:
PDF:
https://aclanthology.org/L16-1305.pdf