Triple

T201018
Position Surface form Disambiguated ID Type / Status
Subject Mickey Rooney E4503 entity
Predicate spouse P13 FINISHED
Object Elaine Devry
Elaine Devry is an American actress known for her film and television roles in the 1950s and 1960s.
E111300 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: Elaine Devry | Statement: [Mickey Rooney, spouse, Elaine Devry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elaine Devry
Context triple: [Mickey Rooney, spouse, Elaine Devry]
  • A. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • B. Deborah Prentice
    Deborah Prentice is an American social psychologist and academic leader known for her work on social norms and for serving as Vice-Chancellor of the University of Cambridge.
  • C. Lynnette Armstrong
    Lynnette Armstrong is a notable individual recognized for achievements significant enough to be associated with the surname Armstrong.
  • D. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • E. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • 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: Elaine Devry
Triple: [Mickey Rooney, spouse, Elaine Devry]
Generated description
Elaine Devry is an American actress known for her film and television roles in the 1950s and 1960s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elaine Devry
Target entity description: Elaine Devry is an American actress known for her film and television roles in the 1950s and 1960s.
  • A. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • B. Deborah Prentice
    Deborah Prentice is an American social psychologist and academic leader known for her work on social norms and for serving as Vice-Chancellor of the University of Cambridge.
  • C. Lynnette Armstrong
    Lynnette Armstrong is a notable individual recognized for achievements significant enough to be associated with the surname Armstrong.
  • D. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • E. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • 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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25be47ea881909c296b30a0d47a65 completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a826b9cb28819096d851acd4350526 completed March 4, 2026, 12:34 p.m.
NEDg Description generation batch_69a83f0495dc8190bee8bfc9f32dafb3 completed March 4, 2026, 2:17 p.m.
NED2 Entity disambiguation (via description) batch_69a83f3698388190b58eec7be7d2a72e completed March 4, 2026, 2:18 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.