Answer Extraction Method Based on BiLSTM and CRF in Q-A System

Answer extraction is an important part of the field of automatic question answering (QA). The traditional answer extraction method relies heavily on contextual semantics, which makes the extraction process consume a lot of time and manpower. Aiming at the question of answer extraction, a method based on the bidirectional long-term memory network conditional random field (Bi-LSTM-CRF) is proposed. This question is extracted in parts from the answer segment. Extract the entity that contains the answer, and then extract the final answer from it. On a valid data set, the accuracy of the experimental results can reach more than 0.6050.