Detect passive voice in headlines
So, your task is to detect the passive voice from sentences. Currently, you have defined some rules to detecting the passive voice and you have noticed that there some exceptions to your defined rules.
Therefore, it would be a good idea to develop a model to predict the probability of a sentence being passive (or active).
You can do this by encoding the sentence as a sequence of words (converted into word embeddings) using a Recurrent Neural Network (RNN) or LSTM. This encode will encode the words into a &quot;hidden representation&quot;. This hidden representation can then be decoded using a neural network with a final softmax output layer which then outputs the probability that the sentence is written in the passive voice and the active voice respectively.
As this would be a supervised learning problem, you would need to label examples of passive- and active-voice sentences.