Triple

T2461553
Position Surface form Disambiguated ID Type / Status
Subject While We're Young E54544 entity
Predicate castMember P1668 FINISHED
Object Charles Grodin E97760 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: Charles Grodin | Statement: [While We're Young, castMember, Charles Grodin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Grodin
Context triple: [While We're Young, castMember, Charles Grodin]
  • A. Charles Grodin chosen
    Charles Grodin was an American actor, comedian, and writer known for his deadpan delivery in films such as "The Heartbreak Kid," "Midnight Run," and the "Beethoven" series.
  • B. Walter Matthau
    Walter Matthau was an American actor renowned for his gruff charm and comedic roles in films such as "The Odd Couple" and "The Bad News Bears."
  • C. Charles Matthau
    Charles Matthau is an American film and television director and producer, and the son of actor Walter Matthau.
  • D. Gene Wilder
    Gene Wilder was an American comic actor and writer best known for his roles in films such as Willy Wonka & the Chocolate Factory, Young Frankenstein, and Blazing Saddles.
  • E. Fred Willard
    Fred Willard was an American comedic actor and improviser known for his deadpan delivery and scene-stealing roles in mockumentaries like "Best in Show" and numerous television comedies.
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11c47408190b10c7f6a151f2db2 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d2b2748190b12611863d8bf4ad completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:44 p.m.