Triple

T12597643
Position Surface form Disambiguated ID Type / Status
Subject Queen for a Day E300772 entity
Predicate host P2592 FINISHED
Object Jack Bailey
Jack Bailey was an American radio and television personality best known for hosting the popular game show "Queen for a Day."
 E997441 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: Jack Bailey | Statement: [Queen for a Day, host, Jack Bailey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Jack Bailey
Context triple: [Queen for a Day, host, Jack Bailey]
  • A. Jack Bailey
    Jack Bailey is a fictional law enforcement officer who serves as the straight-laced partner to the reckless detective Dan Stark in the TV series "The Good Guys."
  • B. Sean Bailey
    Sean Bailey is an American film producer and studio executive known for overseeing major projects at Walt Disney Studios and producing acclaimed films such as "Gone Baby Gone."
  • C. Sam Baldwin
    Sam Baldwin is the widowed architect and devoted father portrayed by Tom Hanks in the romantic comedy film "Sleepless in Seattle."
  • D. Edward Bailey
    Edward Bailey is a retired MI6 agent and skilled operative portrayed by Anthony Hopkins in the action-comedy film "Red 2."
  • E. Jeff Bailey
    Jeff Bailey is the enigmatic private detective and central protagonist of the classic 1947 film noir "Out of the Past."
  • 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: Jack Bailey
Triple: [Queen for a Day, host, Jack Bailey]
Generated description
Jack Bailey was an American radio and television personality best known for hosting the popular game show "Queen for a Day."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Jack Bailey
Target entity description: Jack Bailey was an American radio and television personality best known for hosting the popular game show "Queen for a Day."
  • A. Jack Bailey
    Jack Bailey is a fictional law enforcement officer who serves as the straight-laced partner to the reckless detective Dan Stark in the TV series "The Good Guys."
  • B. Sean Bailey
    Sean Bailey is an American film producer and studio executive known for overseeing major projects at Walt Disney Studios and producing acclaimed films such as "Gone Baby Gone."
  • C. Sam Baldwin
    Sam Baldwin is the widowed architect and devoted father portrayed by Tom Hanks in the romantic comedy film "Sleepless in Seattle."
  • D. Edward Bailey
    Edward Bailey is a retired MI6 agent and skilled operative portrayed by Anthony Hopkins in the action-comedy film "Red 2."
  • E. Jeff Bailey
    Jeff Bailey is the enigmatic private detective and central protagonist of the classic 1947 film noir "Out of the Past."
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954cf33b88190bff339fcd3142cc8 completed April 10, 2026, 7:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671926a7c8190a41725cfde7836b1 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f672d16f8881908c6d5cfed0b3ec3a completed May 2, 2026, 9:55 p.m.
NED2 Entity disambiguation (via description) batch_69f67396fdac8190970068b2c39ad2f7 completed May 2, 2026, 9:58 p.m.
Created at: April 9, 2026, 5:08 p.m.