Triple

T18300567
Position Surface form Disambiguated ID Type / Status
Subject Ray Serve E438347 entity
Predicate builtOnFramework P2012 FINISHED
Object Ray NE NERFINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ray | Statement: [Ray Serve, builtOnFramework, Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray
Context triple: [Ray Serve, builtOnFramework, Ray]
  • A. Ray
    Ray is a masculine given name commonly used in English-speaking countries, often as a short form of Raymond.
  • B. Ray
    Ray is an ancient city near modern-day Tehran in Iran that served as a significant political and cultural center in various Persian empires.
  • C. Ray
    Ray is the optimistic Cajun firefly from Disney’s *The Princess and the Frog*, known for his devotion to his love “Evangeline” and his role in aiding Tiana and Naveen.
  • D. Ray
    Ray is the romantic, Cajun firefly character from Disney’s animated film "The Princess and the Frog," known for his heartfelt song "Ma Belle Evangeline."
  • E. Ray
    Ray is the middle name of American country music singer and actor Kenneth Ray Rogers, better known as Kenny Rogers.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ray
Target entity description: Ray is an open-source distributed computing framework designed for scaling Python applications across clusters for tasks like machine learning, data processing, and reinforcement learning.
  • A. Ray chosen
    Ray is an open-source distributed computing framework designed to scale Python applications for tasks like machine learning, reinforcement learning, and data processing across clusters.
  • B. Ray
    Ray is a masculine given name commonly used in English-speaking countries, often as a short form of Raymond.
  • C. Ray
    Ray is a ruler associated with the House of Buya, known as the sovereign authority over that realm.
  • D. Ray
    Ray is the optimistic Cajun firefly from Disney’s *The Princess and the Frog*, known for his devotion to his love “Evangeline” and his role in aiding Tiana and Naveen.
  • E. Ray
    Ray is an ancient city near modern-day Tehran in Iran that served as a significant political and cultural center in various Persian empires.
  • F. None of above.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: builtOnFramework
Context triple: [Ray Serve, builtOnFramework, Ray]
  • A. builtOn chosen
    Indicates that one entity is constructed, developed, or established using another entity as its base, foundation, or underlying platform.
  • B. isPartOfFramework
    Indicates that one entity functions as a component, module, or element within a larger structured framework or system.
  • C. frameworkFor
    Indicates that one entity serves as a supporting structure, system, or basis that organizes, guides, or enables the development or functioning of another entity.
  • D. frameworkName
    Indicates that a specific framework is identified by the given name.
  • E. createdFrameworkFor
    Indicates that one entity developed or established a foundational structure, system, or methodology that another entity later used or built upon.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5017f63dc819083a675d570620f2f completed April 19, 2026, 4:23 p.m.
PD Predicate disambiguation batch_69e44fdf43d08190bbcfb6b1fe3cc0ee completed April 19, 2026, 3:45 a.m.
Created at: April 10, 2026, 10:35 a.m.