I read this in an article about bidirectional LSTM:
In bidirectional LSTM, each word corresponds to two hidden states, one for each direction. Thus, we concatenate these two hidden states to represent the semantic meaning of a word. Additionally, the last hidden states of the bidirectional LSTM are concatenated to be the sentence vector
Could someone explain what are these two hidden states representing each word, and also clarify what are the last hidden states when representing the sentence?