Triple

T13036331
Position Surface form Disambiguated ID Type / Status
Subject Lou Grant E326569 entity
Predicate appearsIn P795 FINISHED
Object Lou Grant E326569 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: Lou Grant | Statement: [Lou Grant, appearsIn, Lou Grant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lou Grant
Context triple: [Lou Grant, appearsIn, 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. Bill Whitaker
    Bill Whitaker is an American television journalist best known as a longtime correspondent for the CBS news magazine program "60 Minutes."
  • C. 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.
  • D. Mike Wallace
    Mike Wallace was a prominent American broadcast journalist best known as a hard-hitting correspondent on the television news magazine "60 Minutes."
  • E. Drew Pearson
    Drew Pearson is a former NFL wide receiver best known as a star playmaker for the Dallas Cowboys during the 1970s, including his role in the famous "Hail Mary" catch.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97f2a71a0819098bb6cf8a4b2208a completed April 10, 2026, 10:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e269c18481908e0b46c298a946ca completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 8:55 p.m.