Get more out of your text data

IBM Watson® Natural Language Understanding uses deep learning to extract meaning and metadata from unstructured text data. Get underneath your data using text analytics to extract categories, classification, entities, keywords, sentiment, emotion, relations and syntax. Natural Language Understanding is a best-of-breed text analytics service that can be integrated into an existing data pipeline that supports 13 languages depending on the feature. NLU is hosted in Dallas, Washington, D.C., Frankfurt, and Sydney.

• Deploy Watson Natural Language Understanding behind your firewall or on any cloud.
• Train Watson to understand the language of your business and extract customized insights with Watson Knowledge Studio.
• Surface real-time actionable insights to provide your employees with the tools they need to pull meta-data and patterns from massive troves of data.  

Features

Learn more below about how Watson Natural Language Understanding extracts metadata from text such as entities, keywords, categories, sentiment, emotion, relations, syntax and much more.

• **Domain customization: **Train Watson to understand the language of your business and extract customized insights with Watson Knowledge Studio.
• **Text analytics: **Surface real-time actionable insights to provides your employees with the tools they need to pull meta-data and patterns from massive troves of data.
• **Deploy anywhere: **Deploy Watson Natural Language Understanding behind your firewall or on any cloud.
• **Entities: **Detect people, places, events, and other types of entities mentioned in your content using our out-of-the-box capabilities.
• **Categories (Beta): **Categorize your data with granularity using a five-level classification hierarchy.
• **Classifications: **Classify text with custom labels to automate workflows, extract insights, and improve search and discovery.
• **Concepts: **Identify high-level concepts that aren’t necessarily directly referenced in your content.
• **Emotions: **Extract emotions (joy, anger, sadness, fear, and other feelings) conveyed by specific target phrases or by the document as a whole.
• **Sentiment (Beta): **Analyze the sentiment (positive, negative, or neutral) towards specific target phrases and of the document as a whole.
• **Relations: **Understand the relationship between two entities within your content and identify the type of relation.
• **Metadata: **Quickly extract information from a document such as author, title, images, and publication dates.
• **Semantic roles: **Parse sentences into subject-action-object form and identify entities and keywords that are subjects or objects of an action.