What is Natural Language Generation?
Natural Language Generation, otherwise known as NLG, is a software process that utilizes Natural Language Processing (NLP) to produce natural written or spoken language from structured and unstructured data. The most common methods of NLG are extractive and abstractive. An extractive approach takes a large body of text, pulls out sentences that are most representative of key points, and concatenates them to generate a summary of the larger text. An abstractive approach creates novel text by identifying key concepts and then generating new language that attempts to capture the key points of a larger body of text intelligibly.
Why is Natural Language Generation important?
Unbeknownst to the reader, NLG techniques are commonly used in popular data analysis and reporting outlets, such as sports and financial reports. In these applications, numeric values from a box score or financial statement are populated into a machine-generated article that describes those figures or scores. This format helps make quantitative, structured data more storylike. Advancements in NLP and NLU have opened the door to introducing NLG processes into the world of Customer Experience Management. Now, analysis of millions of customer conversations can be transformed into machine-generated summaries tailored for specific use cases making data consumption more convenient and palatable for larger audiences.
How does Clarabridge use NLG?
Unstructured data can pose many challenges for NLG because it can be more difficult for a machine to determine the most meaningful information from large bodies of text. At Clarabridge, we take a more prescriptive and hands-on approach to NLG in order to accomplish more human-like and meaningful storytelling around unstructured data. By blending extractive and abstractive methods into a hybrid based approach, Clarabridge Automated Narratives deliver an ideal balance of relevancy and interpretability which are tailored to your business needs. This can be used to automate post-interaction notes, summarize insights, synthesize employee performance, and more.