Answers that are "rejected" in the manual mode will be excluded when you train – but you can use it to mark issues with the text, like problematic tokenization that you may want to fix etc. See here for more details:
Related topics
Topic | Replies | Views | Activity | |
---|---|---|---|---|
Recommended text length for training NER models in spaCy | 10 | 3009 | June 13, 2022 | |
Annotating custom entities in job descriptions | 9 | 1159 | June 2, 2019 | |
Help with building NER for job descriptions | 6 | 2914 | December 27, 2018 | |
Questionable results from NER - we must be doing something wrong
|
5 | 4344 | August 30, 2018 | |
NER Training for Corporate Names | 22 | 11385 | September 4, 2019 |