International business machines corporation (20240289371). AUTOMATED ENRICHMENT OF ENTITY DESCRIPTIONS IN UNSTRUCTURED TEXT simplified abstract

From WikiPatents
Jump to navigation Jump to search

AUTOMATED ENRICHMENT OF ENTITY DESCRIPTIONS IN UNSTRUCTURED TEXT

Organization Name

international business machines corporation

Inventor(s)

[[:Category:Marcos Mart�nez Galindo of Dublin (IE)|Marcos Mart�nez Galindo of Dublin (IE)]][[Category:Marcos Mart�nez Galindo of Dublin (IE)]]

Leopold Fuchs of Stuttgart (DE)

Gabriele Picco of Dublin (IE)

Thanh Lam Hoang of Maynooth (IE)

Vanessa Lopez Garcia of Dublin (IE)

Marco Luca Sbodio of Castaheany (IE)

AUTOMATED ENRICHMENT OF ENTITY DESCRIPTIONS IN UNSTRUCTURED TEXT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240289371 titled 'AUTOMATED ENRICHMENT OF ENTITY DESCRIPTIONS IN UNSTRUCTURED TEXT

Simplified Explanation: The patent application describes a method for automatically enriching the descriptions of an entity mentioned in a sentence corpus by generating multiple enriched descriptions, ranking them based on a machine learning model, and annotating the sentence corpus with the selected enriched descriptions.

  • **Key Features and Innovation:**
   - Generation of multiple enriched descriptions for an entity
   - Ranking of enriched descriptions using a machine learning model
   - Annotation of sentence corpus with selected enriched descriptions
  • **Potential Applications:**
   - Natural language processing
   - Information retrieval systems
   - Content generation tools
  • **Problems Solved:**
   - Enhancing the accuracy of entity descriptions
   - Improving the quality of annotated data
   - Streamlining the process of enriching entity descriptions
  • **Benefits:**
   - Increased efficiency in generating enriched descriptions
   - Improved relevance of entity descriptions
   - Enhanced performance of machine learning models
  • **Commercial Applications:**
   - "Automated Entity Description Enrichment System for Natural Language Processing Applications"
  • **Prior Art:**
   - Researchers can explore prior art related to machine learning models for text annotation and natural language processing techniques.
  • **Frequently Updated Research:**
   - Stay updated on advancements in machine learning models for text annotation and natural language processing.

Questions about Entity Description Enrichment: 1. How does the machine learning model determine the likelihood of an enriched description correctly describing the entity? 

   - The machine learning model uses various features to assess the accuracy of enriched descriptions, such as semantic similarity and context analysis.

2. What are the potential challenges in implementing this automated entity description enrichment system in real-world applications? 

   - Some challenges may include handling diverse types of entities, ensuring scalability, and adapting to evolving language patterns.


Original Abstract Submitted

automatically enriching the descriptions of an entity mentioned in a sentence corpus includes generating multiple enriched descriptions corresponding to a label of the entity. each of the multiple enriched descriptions is ranked. the ranking is generated by a machine learning model that is configured to determine a likelihood that an enriched description correctly describes the entity. the sentence corpus are annotated by coupling each mention of the entity with one or more of the enriched descriptions. the one or more enriched descriptions are selected based on the ranking. as annotated, the sentence corpus can be output.

Retrieved from "http://wikipatents.org/index.php?title=International_business_machines_corporation_(20240289371)._AUTOMATED_ENRICHMENT_OF_ENTITY_DESCRIPTIONS_IN_UNSTRUCTURED_TEXT_simplified_abstract&oldid=223897"