Academy & Industry Research Collaboration Center (AIRCC)

Volume 11, Number 23, December 2021

ANEC: Artificial Named Entity Classifier based on BI-LSTM for an AI-based Business Analyst


Taaniya Arora, Neha Prabhugaonkar, Ganesh Subramanian and Kathy Leake, Crux Intelligence, USA


Business users across enterprises today rely on reports and dashboards created by IT organizations to understand the dynamics of their business better and get insights into the data. In many cases, these users are underserved and do not possess the technical skillset to query the data source to get the information they need. There is a need for users to access information in the most natural way possible. AI-based Business Analysts are going to change the future of business analytics and business intelligence by providing a natural language interface between the user and data. This natural language interface can understand ambiguous questions from users, the intent and convert the same into a database query. One of the important elements of an AI-based business analyst is to interpret a natural language question. It also requires identification of key business entities within the question and relationship between them to generate insights. The Artificial Named Entity Classifier (ANEC) helps us take a huge step forward in that direction by not only identifying but also classifying entities with the help of the sequence recognising prowess of BiLSTMs.


Named Entity Recognition System, Natural Language Processing , Business Analytics, Question Answering Systems, Bi-directional LSTMs.