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Nov 14, 2021 at 12:14 answer added Archana David timeline score: 0
Nov 12, 2021 at 21:34 answer added keiv.fly timeline score: 0
Nov 10, 2021 at 15:36 comment added Erwan @bratao as far as I know this is exactly what sequence labeling does. You could also look into methods used for event detection, it looks similar.
Nov 10, 2021 at 14:13 comment added bratao @Erwan and Eulenfuchswiesel this is just a example. I want to be able to model a classifier that takes the previous classification in consideration using something like a CRF or Beam Search. It must have something in the literature about it, but I can´t find
Nov 10, 2021 at 14:11 history edited bratao CC BY-SA 4.0
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Nov 10, 2021 at 8:48 comment added Eulenfuchswiesel I guess the pronouns are the problem. "Her" can refer to the boss or the girl. If the pronoun got replaced, the problem would be a lot easier. So maybe as a start, replace all pronouns by whatever noun preceeded, then try the prediction again.
Nov 9, 2021 at 23:14 comment added Erwan At first sight sequence labelling seems a good idea to me. What is strange in your data is that apparently all the conversations are mixed? Normally I would expect the first two to be part of one conversation and the last two to belong to another.
S Nov 9, 2021 at 17:12 history bounty started bratao
S Nov 9, 2021 at 17:12 history notice added bratao Draw attention
Nov 7, 2021 at 13:54 answer added Brian Spiering timeline score: 0
S Nov 6, 2021 at 19:44 review First questions
Nov 7, 2021 at 8:05
S Nov 6, 2021 at 19:44 history asked bratao CC BY-SA 4.0