Triple

T21862941
Position Surface form Disambiguated ID Type / Status
Subject John Tesh E539812 entity
Predicate employer P7 FINISHED
Object Entertainment Tonight NE NERFINISHED

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: Entertainment Tonight | Statement: [John Tesh, employer, Entertainment Tonight]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Entertainment Tonight
Context triple: [John Tesh, employer, Entertainment Tonight]
  • A. Entertainment Tonight chosen
    Entertainment Tonight is a long-running American entertainment news television program that covers celebrity news, Hollywood events, and the film and television industry.
  • B. E!
    E! is an American cable television network best known for its entertainment news, celebrity gossip, and pop culture–focused reality programming.
  • C. MTV News
    MTV News was the news division of the MTV television network, known for covering music, pop culture, and youth-oriented current events.
  • D. Inside Edition
    Inside Edition is a long-running American television newsmagazine program that focuses on tabloid-style news, celebrity stories, and human-interest features.
  • E. Good Morning America
    Good Morning America is a long-running American morning television show on ABC that features news, interviews, and lifestyle segments.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47829648190bbe2d1d7033768ec completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f0d63beb00819092b8ec3a8ef55a39 completed April 28, 2026, 3:46 p.m.
Created at: April 16, 2026, 6:56 p.m.