Triple

T1336785
Position Surface form Disambiguated ID Type / Status
Subject Wyly Theatre E28769 entity
Predicate namedAfter P63 FINISHED
Object Dee Wyly E154826 NE FINISHED

How this triple was built (2 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: Dee Wyly | Statement: [Wyly Theatre, namedAfter, Dee Wyly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dee Wyly
Context triple: [Wyly Theatre, namedAfter, Dee Wyly]
  • A. Pat Tilley
    Pat Tilley is a former American football wide receiver best known for his productive NFL career with the St. Louis Cardinals in the 1970s and early 1980s.
  • B. Cheryl Alley
    Cheryl Alley, also known as Cheryl Howard, is an American writer and actress best known as the longtime wife of filmmaker Ron Howard.
  • C. Charles Wyly chosen
    Charles Wyly was an American billionaire businessman and philanthropist known for his major contributions to arts and cultural institutions, particularly in Dallas, Texas.
  • D. Christiana Wyly
    Christiana Wyly is an American environmental advocate and heiress known for her work in sustainability and philanthropy.
  • E. Loretta Rogers
    Loretta Rogers is a Canadian philanthropist and longtime director of Rogers Communications, known as the widow of company founder Ted Rogers.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1edda1c81909a1149b254b0d57e completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acce660ccc8190abc6cdceaf09101c completed March 8, 2026, 1:18 a.m.
Created at: March 1, 2026, 7:55 p.m.