: Vocabulario de PLN: manual annotation

computational linguistics > syntax > annotation > manual annotation

manual annotation

Compared with existing approaches the proposed method requires less manual annotations. (Liu, Li, Zhang, Yang & Zhou, 2019)
In order to reduce the manual annotation we got rid of trivial cases of irrelevant tweets i.e. tweets that do not contain any mention of the author of the tweet itself. (Wiegand, Wilm & Markert, 2022)
Since manual annotation is such an expensive operation and relatively few resources are currently available evaluation is often limited to either a single resource or the calculation of precision. (Rigouts Terryn, Hoste, Drouin & Lefever, 2020)
These datasets are collected in a multitude of ways often involving manual annotations by native speakers. (Khashabi, Cohan, Shakeri, Hosseini, Pezeshkpour, Alikhani, Aminnaseri, Bitaab, Brahman, Ghazarian, Gheini, Kabiri, Mahabagdi, Memarrast, Mosallanezhad, Noury, Raji, Rasooli, Sadeghi, Azer, Samghabadi, Shafaei, Sheybani, Tazarv & Yaghoobzadeh, 2021)
To speed up manual annotation we tagged tweets by using the taggers and then we corrected the output of the taggers to construct a gold standard. (Albogamy & Ramsay, 2015)

http://data.loterre.fr/ark:/67375/8LP-LWS9HD2M-F

RDF/XML TURTLE JSON-LD última modificación 6/6/24

Loterre