Relation Extraction
Make use of our NLP expertise to help AI extract relationships between entities in unstructured sources, such as raw text. Coral Mountain Data provides businesses working on NLP prototypes with supervised relation extraction from text. We perform relation extraction using NLP techniques that allow us to identify entity relationships in the text.
Core Capabilities
Advanced technology built for enterprise scale.
Text Annotation
The process of annotation for relation extraction in NLP involves assigning labels to phrases or words in a sentence or document that describe their relationship. Our text annotation experts can help build information extraction systems, or create knowledge bases out of the text.
Open Relationship Extraction
Open relationship extraction involves extracting relationships that are not explicitly stated in the text. It can generate knowledge graphs for accurate information presentation, service recommendation, and question answering.
Supervised Relation Extraction
Training the model on labeled data constitutes supervised learning. With considerable expertise in NLP models and relation extraction, our experts know what it takes to develop a model that recognizes relationships between two entities in a text.
Targeted Relationship Extraction
A targeted relationship extraction method identifies specific relationships among entities in a text. We can identify entities and their relationships within the text using automated systems and manual methods.
Entity Relationship Extraction (ERE)
Entity Relationship Extraction involves extracting structured information from unstructured text to identify relationships among entities such as people, products, and places using rule-based and machine-learning techniques.
Quality on a Promise
Our team is committed to delivering high-quality Text Annotations. Our training data is therefore tailored for the applications of our clients.
Uncompromised Data Security
Data security and confidentiality are of utmost importance to us. At all points in the annotation process, our team ensures that no data breaches occur.
Proven Applications
See how industry leaders are leveraging our solutions in production environments.
Discuss Your Use Case
Medical
In order to build a medical database, pharmaceutical companies can use relationship extraction-based AI to find interactions/relationships among drugs and medicines.
Social Media
With relationship extraction, social media companies can design AI that recommends relevant pages and communities to users based on relationships between people, places, and organizations.
Information Technology
Search engines can utilize relationship extraction to build a searchable knowledge base and develop AI to recommend user pages with content similar to their search terminologies.