entityRecognition.py 文件源码

def predict(utterance):
    try:
        tagged = []
        finallist = []
        parsed = nlp(utterance)
        for i in range(len(parsed)):
            tagged.append((str(parsed[i]),parsed[i].tag_))
        finallist.append(tagged)
        test = [sent2features(s) for s in finallist]
        if(os.path.isfile("crfModel/classifier.pkl")):
            crf = joblib.load("crfModel/classifier.pkl")
        else:
            return {'success':False,'message':'Please Train the model first'}
        predicted = crf.predict(test)
        entityList = extractEntities(predicted[0],tagged)
        return {'success':True,'entitiesPredicted':entityList}
    except Exception as ex:
        return {'success':False,'message':'Error while pediction - '+str(ex)}