Triple

T15681209
Position Surface form Disambiguated ID Type / Status
Subject Ray Stantz E377580 entity
Predicate nickname P55 FINISHED
Object Ray
Ray is the affectionate nickname of Ray Stantz, the enthusiastic and nerdy parapsychologist from the Ghostbusters franchise.
E1170689 NE FINISHED

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 Stantz, nickname, Ray]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ray
Context triple: [Ray Stantz, nickname, Ray]
  • A. Ray
    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 the central figure in Claude McKay’s novel "Home to Harlem," embodying the intellectual, conflicted perspective on Black identity and urban life during the Harlem Renaissance.
  • C. Ray
    Ray is the protagonist of the novel "The Keep," around whom the story’s central psychological and narrative tensions revolve.
  • 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 the romantic, Cajun firefly character from Disney’s animated film "The Princess and the Frog," known for his heartfelt song "Ma Belle Evangeline."
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ray
Triple: [Ray Stantz, nickname, Ray]
Generated description
Ray is the affectionate nickname of Ray Stantz, the enthusiastic and nerdy parapsychologist from the Ghostbusters franchise.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ray
Target entity description: Ray is the affectionate nickname of Ray Stantz, the enthusiastic and nerdy parapsychologist from the Ghostbusters franchise.
  • A. 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.
  • 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 the romantic, Cajun firefly character from Disney’s animated film "The Princess and the Frog," known for his heartfelt song "Ma Belle Evangeline."
  • D. Ray
    Ray is the protagonist of the novel "The Keep," around whom the story’s central psychological and narrative tensions revolve.
  • E. Ray
    Ray is the middle name of Lola Ray Facinelli, a member of the Facinelli family.
  • F. None of above. chosen

Provenance (5 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f306a1c8190a819541a3cc51f5a completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ece07608190a705f108c8c2979a completed May 9, 2026, 5:28 p.m.
NEDg Description generation batch_69ff6fb61144819085460226d406161d completed May 9, 2026, 5:32 p.m.
NED2 Entity disambiguation (via description) batch_69ff705b1ea08190bf08b99c19715e57 completed May 9, 2026, 5:35 p.m.
Created at: April 10, 2026, 4:16 a.m.