Would like to understand whether prodigy tool supports the following,
- TSV file (as input).
- Active Learning on NER side.
- Can a CoreNLP NER output (not necessarily to be one derived from prodigy) be fed to the tool and rework on the NER outputs (for example – can a tag ‘ORG’ be changed to ‘NON_ORG’ wherever applicable).
Looking forward to hearing from you.
Thanks and Regards
Hi @leventm , welcome to Prodigy!
- One way you can load TSV is to use the CSV loader and pass a tab as its delimiter.
- You can perform active learning using the
ner.teach recipe. It updates a model in the loop, and based on your annotations, Prodigy will decide the best next question to annotate.
- Yes that should be possible. Once you have the CoreNLP NER output, you need to convert them into a format that Prodigy accepts and run the appropriate NER recipe (
ner.manual for "standard NER" and
ner.teach for an active-learning powered one). You can customize the tags by passing arguments to the