#MeTooMaastricht: Building a chatbot to assist survivors of sexual harassment
Table 1: Validation results for accuracy
['Classifier', 'Location', 'Date', 'Time']
To receive comparable results for the three different used NER models namely Stanford, BERT trained on CoNLL corpora and BERT trained on Ontonotes we generated for each report template 100 variations with randomly picked named entities and used them as input for the models. It can be seen that both BERT models deliver reasonable results for the identification of location entities. However the BERT model trained on CoNLL corpora is not able to identify any information about the date or time. However the results produced by BERT are significantly better than the results from the Stanford NER model. The drop of accuracy for time information in the BERT model can be explained by looking at the returned values. Apparently there is some confusion between date and time information.