I'm getting this error when running fit and aggregate. It seems to be related to documents without any annotations by the labelling functions.
When tying it with the documents in my data set that have annotations, it works fine. However, when running it on specific ones where the labelling functions did not detect anything, it throws this error.
Is this a known issue and is there any way to fix this?
Thanks!
`docs = list(LF1.pipe(train_data))
docs = list(LF2.pipe(docs))
docs = list(LF3.pipe(docs))
docs = list(LF4.pipe(docs))
docs = list(LF5.pipe(train))
ner_model = skweak.spacy.ModelAnnotator("spacy", "en_core_web_sm")
docs = list(ner_model.pipe(docs))
I'm getting this error when running fit and aggregate. It seems to be related to documents without any annotations by the labelling functions. When tying it with the documents in my data set that have annotations, it works fine. However, when running it on specific ones where the labelling functions did not detect anything, it throws this error. Is this a known issue and is there any way to fix this? Thanks! `docs = list(LF1.pipe(train_data)) docs = list(LF2.pipe(docs)) docs = list(LF3.pipe(docs)) docs = list(LF4.pipe(docs)) docs = list(LF5.pipe(train)) ner_model = skweak.spacy.ModelAnnotator("spacy", "en_core_web_sm") docs = list(ner_model.pipe(docs))
hmm = skweak.aggregation.HMM("hmm",["A", "NOT_A"], sequence_labelling=False) hmm.fit_and_aggregate(docs)``