Triple

T15046887
Position Surface form Disambiguated ID Type / Status
Subject Daisy Carter E379251 entity
Predicate hasFirstName P17 FINISHED
Object Daisy E177425 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: Daisy | Statement: [Daisy Carter, hasFirstName, Daisy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daisy
Context triple: [Daisy Carter, hasFirstName, Daisy]
  • A. Daisy
    Daisy is a themed parking section within the Mickey & Friends Parking Structure at the Disneyland Resort, named after the Disney character Daisy Duck.
  • B. Daisy
    Daisy is a central character in Margaret Atwood's dystopian novel "The Testaments," whose perspective helps reveal the inner workings and resistance within the totalitarian regime of Gilead.
  • C. Daisy
    Daisy is the central protagonist of "The Mystery Series," around whom the stories' investigations and adventures revolve.
  • D. Daisy chosen
    Daisy is a feminine given name commonly associated with the daisy flower and often used in English-speaking countries.
  • E. Daisy
    Daisy is a small rural community located within Evans County in the U.S. state of Georgia.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda8e64e48190873104a02a676ff3 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe9de73614819098b7a88624407d0e completed May 9, 2026, 2:37 a.m.
Created at: April 10, 2026, 3 a.m.