Triple

T22467367
Position Surface form Disambiguated ID Type / Status
Subject Lance Guest E555389 entity
Predicate participatedIn P149 FINISHED
Object Lou Grant 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: Lou Grant | Statement: [Lance Guest, participatedIn, Lou Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lou Grant
Context triple: [Lance Guest, participatedIn, Lou Grant]
  • A. Lou Grant chosen
    Lou Grant is a gruff but warm-hearted television news producer, portrayed by Ed Asner, who became one of American TV’s most iconic newsroom bosses and later headlined his own dramatic spin-off series.
  • B. Hank McDodd
    Hank McDodd is a character from Dr. Seuss's "Horton Hears a Who!" and its adaptations, depicted as one of the many children in the McDodd family living in Whoville.
  • C. Bill Whitaker
    Bill Whitaker is an American television journalist best known as a longtime correspondent for the CBS news magazine program "60 Minutes."
  • D. Brian Lamb
    Brian Lamb is an American journalist and television executive best known as the founder and longtime CEO of the public affairs network C-SPAN.
  • E. Mike Wallace
    Mike Wallace was a prominent American broadcast journalist best known as a hard-hitting correspondent on the television news magazine "60 Minutes."
  • 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_69e11e51fdec8190adfdf9f8a6362221 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b84e4a88190b6fbfdbd754ba1c5 completed April 29, 2026, 1:14 a.m.
Created at: April 16, 2026, 8:48 p.m.