@techreport{TR-IC-PFG-23-55,
   number = {IC-PFG-23-55},
   author  =  {Andreis  Gustavo  Malta  {Purim}  and  Julio Cesar {dos
                   Reis}},
   title = {{Active Learning for Natural Language Data Annotation}},
   month = {December},
   year = {2023},
   institution = {Institute of Computing, University of Campinas},
   note = {In English, 16 pages.
    \par\selectlanguage{english}\textbf{Abstract}
       Developing   task-oriented   conversational   systems  requires 
       substantial  annotated  data,  posing  a  challenge  in Natural
       Language  Processing (NLP). Manual annotation is time-consuming
       and  error-prone, hindering progress for smaller AI teams. This
       work  presents  a  novel  Dialog  Annotation  Methodology and a
       ready-to-use   adaptable   software   tool  offering  automatic 
       annotation.  The  automatic  annotation  model  is  based  on a
       cascade of Machine Learning and Large Language Model annotation
       to   annotate  entities  and  intentions  in  natural  language 
       dialogs.
  }
}