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Using InterSystems UIMA

Integrate UIMA engines with InterSystems IRIS to generate and store text annotations.

Updated Feb 2, 2026
Search Tags:#data processing#nlp#text analysis#annotation#intersystems iris#uima
One-click install
npx skills add https://github.com/sorodriguezz/skills-objectscript --skill using-intersystems-uima
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Using InterSystems UIMA
Source: https://github.com/sorodriguezz/skills-objectscript/tree/main/skills/using-intersystems-uima
Command: npx skills add https://github.com/sorodriguezz/skills-objectscript --skill using-intersystems-uima

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of extracting meaningful information and annotations from unstructured text data by leveraging the Universal Natural Language Processing Architecture (UIMA) framework. It enables the integration of various text analysis technologies to process and store annotations efficiently.

Core Features & Use Cases

  • UIMA Integration: Facilitates the use of InterSystems IRIS Natural Language Processing (NLP) and third-party UIMA-compliant analysis engines.
  • Annotation Generation: Creates annotations (e.g., named entities, concepts, relations) for source text, storing them separately from the original data.
  • Pipeline Architecture: Supports the creation of analysis pipelines where multiple UIMA engines process data sequentially.
  • Annotation Store: Provides a persistent, SQL-based storage for annotations, allowing for easier querying and analysis compared to traditional XML formats.
  • Use Case: Analyze customer feedback from support tickets to automatically identify product issues, sentiment, and key topics, storing these insights in a structured format for reporting and product improvement.

Quick Start

Configure a UIMA functional index on the 'FullArticle' column of the 'NYT.Articles' table to process text data using the 'iKnowEngine.xml' descriptor.

Frequently Asked Questions about Using InterSystems UIMA

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I process unstructured text data for insights extraction using InterSystems IRIS?▼

You can process unstructured text data in InterSystems IRIS by using UIMA pipelines to generate and store annotations like named entities and concepts in a dedicated SQL-based annotation store.

Can I use third-party NLP engines with InterSystems IRIS for text analysis?▼

Yes, you can use third-party UIMA-compliant analysis engines alongside InterSystems NLP within a sequential pipeline architecture to perform advanced text analysis and annotation.

How do I store NLP annotations in SQL instead of XML?▼

This Skill provides a persistent, SQL-based annotation store for UIMA annotations, allowing you to query and analyze extracted text insights directly instead of relying on traditional XML formats.

What is the best way to analyze customer feedback and support tickets for product issues?▼

The best way to analyze customer feedback is to configure a UIMA functional index on your text columns, automatically identifying product issues, sentiment, and key topics for structured reporting.

Does InterSystems UIMA support pipeline architectures for sequential text analysis?▼

Yes, it supports the creation of analysis pipelines where multiple UIMA engines process unstructured data sequentially to generate and store comprehensive text annotations.

How do I configure a UIMA functional index on an SQL table column?▼

You can configure a UIMA functional index on a specific text column, such as 'FullArticle', using an XML descriptor like 'iKnowEngine.xml' to process and annotate text data.

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