En Sparv-plugin som möjliggör upptäckt och annotering av personlig information i svenska texter, särskilt L2 uppsatser (observera att den här annoteringen fungerar betydligt sämre för andra domäner, men modellerna som används nu kommer sannolikt att uppdateras). Den här modellen garanterar inte att alla personliga uppgifter i texten upptäcks. Använd den aldrig utan översikt av en människa (human-in-the-loop).
Standardreferens
Maria Irena Szawerna, Simon Dobnik, Ricardo Muñoz Sánchez, and Elena Volodina. 2025. The Devil’s in the Details: the Detailedness of Classes Influences Personal Information Detection and Labeling. In Proceedings of the Joint 25th Nordic Conference on Computational Linguistics and 11th Baltic Conference on Human Language Technologies (NoDaLiDa/Baltic-HLT 2025), pages 697–708, Tallinn, Estonia. University of Tartu Library. https://aclanthology.org/2025.nodalida-1.70/
Analyscitering
Språkbanken Text. sbx-swe-pi_detection-sparv [Analysis]. Språkbanken Text. https://doi.org/10.23695/6wp0-ds77

Exempel
This analysis is used with Sparv. Check out Sparv's quick start guide to get started!
To use this analysis, add the following line under export.annotations
in the Sparv corpus configuration file:
- <token>:sbx_pi_detection.pi # None
In order to use this plugin you need to add the following setting to your Sparv corpus configuration file with the appropriate argument (basic, basic_iob, general, general_iob, detailed, or detailed_iob):
sbx_pi_detection:
annotation_level: general
You also need to install the following plugin: sbx_pi_detection.
For general information on how to install plugins, see here.
For more info on how to use Sparv, check out the Sparv documentation.
Example output:
<token pi="O">Jag</token>
<token pi="O">heter</token>
<token pi="personal_name">Maria</token>
<token pi="O">.</token>