Triple

T14702761
Position Surface form Disambiguated ID Type / Status
Subject Darling E345347 entity
Predicate pet P8711 FINISHED
Object Danielle unclear NED1 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: Danielle | Statement: [Darling, pet, Danielle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danielle
Context triple: [Darling, pet, Danielle]
  • A. Danielle
    "Danielle" is a work created by Sarah Churchill, known as part of her contributions to the arts.
  • B. Danielle
    Danielle is the young prodigy and central superheroine of the novel "Chronicles of a Superheroine," known for using her intelligence and creativity to tackle global challenges.
  • C. Danielle
    Danielle is the given first name of American actress and producer Riley Keough, known for her roles in films like "Mad Max: Fury Road" and the series "Daisy Jones & The Six."
  • D. Danielle
    Danielle is a feminine given name commonly used in English- and French-speaking countries, derived from the Hebrew name Daniel.
  • E. Danielle
    Danielle is a fictional daughter of a lady character, appearing as part of a narrative family relationship in a work of fiction.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb6071e5c8190bb5509c859135c2d completed April 14, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb8221a4819098937018f24a0b44 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:28 a.m.