NLP is a technology that allows chatbots to comprehend natural language commands and derive meaning from user input, be it text or voice.
Make your chatbots more intelligent – unlike traditional chatbots that deliver scripted, predefined answers, an NLP-powered chatbot understands the intent, entity, and context of the user’s query and delivers more relevant responses. NLP technology has led to the wide acceptance and adoption of chatbots among employees and customers alike.
BotCore, a chatbot builder platform, processes user input with an advanced NLP engine that recognizes contextual user intent and captures the entities with high accuracy.
BotCore’s NLP chatbots extract information from users’ utterances. These could be multiple sentences processed individually or simultaneously, depending on the user’s request.
BotCore’s chatbots correctly determine the lemma and intent of the user’s request. This is the first step in understanding the utterances and carrying out a further interaction with the user.
BotCore’s NLP bots are designed to automatically extract important entities in the user’s message in order to carry out the request of the user. These entities include elements like date, time, location, product categories, and much more.
Bots are trained with Deep Neural Networks and machine learning (ML) technologies, to determine user intent from a set of sample statements for each intent.
NLP liaises between incoming user-generated messages and the bot-generated response, thus successfully interpreting language variations and nuances including morphemes, slang, and contextual variations.
BotCore’s NLP bots are capable of handling all types of conversations – simple or complex – including interruptions, clarifications, entity modifications, multiple requests, etc., without losing the context of the dialogue.
Our intelligent bots can analyze the emotions of the users, using sentiment analysis and tone processing, and suitably modify the direction of the interaction by changing the style of responses or handing over to a human agent for further support.
This is the process that reduces a word to just its word stem and eliminates any prefixes or suffixes that are affixed to it. We can also group related words together based on their lemma or dictionary form.
POS tagging helps the chatbot to understand the input text and assign parts of speech or any other token to each word in a sentence.
Customers expect personalized experiences. NLP-enabled chatbots can process large sums of data quickly and respond to customer queries in a personalized manner.
BotCore’s NLP bots have advanced machine learning capabilities that can learn from past conversations and errors and improve the user experience in the future conversations
Chatbots need less training data to understand natural language. They are faster and easier to train due to a low-code user interface that uses built-in and visual templates.