TY - GEN
T1 - Lightweight grammatical annotation in the TEI
T2 - 11th International Conference on Language Resources and Evaluation, LREC 2018
AU - Bański, Piotr
AU - Haaf, Susanne
AU - Mueller, Martin
N1 - Publisher Copyright:
© LREC 2018 - 11th International Conference on Language Resources and Evaluation. All rights reserved.
PY - 2019
Y1 - 2019
N2 - In mid-2017, as part of our activities within the TEI Special Interest Group for Linguists (LingSIG), we submitted to the TEI Technical Council a proposal for a new attribute class that would gather attributes facilitating simple token-level linguistic annotation. With this proposal, we addressed community feedback complaining about the lack of a specific tagset for lightweight linguistic annotation within the TEI. Apart from @lemma and @lemmaRef, up till now TEI encoders could only resort to using the generic attribute @ana for inline linguistic annotation, or to the quite complex system of feature structures for robust linguistic annotation, the latter requiring relatively complex processing even for the most basic types of linguistic features. As a result, there now exists a small set of basic descriptive devices which have been made available at the cost of only very small changes to the TEI tagset. The merit of a predefined TEI tagset for lightweight linguistic annotation is the homogeneity of tagging and thus better interoperability of simple linguistic resources encoded in the TEI. The present paper introduces the new attributes, makes a case for one more addition, and presents the advantages of the new system over the legacy TEI solutions.
AB - In mid-2017, as part of our activities within the TEI Special Interest Group for Linguists (LingSIG), we submitted to the TEI Technical Council a proposal for a new attribute class that would gather attributes facilitating simple token-level linguistic annotation. With this proposal, we addressed community feedback complaining about the lack of a specific tagset for lightweight linguistic annotation within the TEI. Apart from @lemma and @lemmaRef, up till now TEI encoders could only resort to using the generic attribute @ana for inline linguistic annotation, or to the quite complex system of feature structures for robust linguistic annotation, the latter requiring relatively complex processing even for the most basic types of linguistic features. As a result, there now exists a small set of basic descriptive devices which have been made available at the cost of only very small changes to the TEI tagset. The merit of a predefined TEI tagset for lightweight linguistic annotation is the homogeneity of tagging and thus better interoperability of simple linguistic resources encoded in the TEI. The present paper introduces the new attributes, makes a case for one more addition, and presents the advantages of the new system over the legacy TEI solutions.
KW - Lightweight annotation
KW - Linguistic annotation
KW - TEI
KW - TEI LingSIG
UR - http://www.scopus.com/inward/record.url?scp=85059882259&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059882259&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85059882259
T3 - LREC 2018 - 11th International Conference on Language Resources and Evaluation
SP - 1795
EP - 1802
BT - LREC 2018 - 11th International Conference on Language Resources and Evaluation
A2 - Isahara, Hitoshi
A2 - Maegaard, Bente
A2 - Piperidis, Stelios
A2 - Cieri, Christopher
A2 - Declerck, Thierry
A2 - Hasida, Koiti
A2 - Mazo, Helene
A2 - Choukri, Khalid
A2 - Goggi, Sara
A2 - Mariani, Joseph
A2 - Moreno, Asuncion
A2 - Calzolari, Nicoletta
A2 - Odijk, Jan
A2 - Tokunaga, Takenobu
PB - European Language Resources Association (ELRA)
Y2 - 7 May 2018 through 12 May 2018
ER -