Triple

T13104504
Position Surface form Disambiguated ID Type / Status
Subject Natalie Morales E310808 entity
Predicate portrayed P1668 FINISHED
Object Claire Lacoste in The Grinder E1013336 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: Claire Lacoste in The Grinder | Statement: [Natalie Morales, portrayed, Claire Lacoste in The Grinder]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Claire Lacoste in The Grinder
Context triple: [Natalie Morales, portrayed, Claire Lacoste in The Grinder]
  • A. Claire Lacoste chosen
    Claire Lacoste is a fictional character from the television comedy series "The Grinder."
  • B. Julie Clary
    Julie Clary was a French noblewoman who became Queen consort of Naples and later of Spain through her marriage into the Bonaparte family.
  • C. Claudine Acou
    Claudine Acou is best known as the wife of legendary Belgian cyclist Eddy Merckx.
  • D. Claudine Denosse
    Claudine Denosse was the wife of the prominent 16th-century Reformed theologian and Calvinist leader Theodore Beza.
  • E. Claire Marino
    Claire Marino is the wife of Hall of Fame NFL quarterback Dan Marino and is known for her long-standing involvement in charitable and community work alongside him.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98153255c8190b6ab64ac0c4716f8 completed April 10, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6e277b89c8190a0d895eb46836525 completed May 3, 2026, 5:51 a.m.
Created at: April 9, 2026, 9:05 p.m.