Triple

T22273067
Position Surface form Disambiguated ID Type / Status
Subject Faizon Love E550526 entity
Predicate appearedIn P795 FINISHED
Object Zookeeper NE NERFINISHED

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: Zookeeper | Statement: [Faizon Love, appearedIn, Zookeeper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zookeeper
Context triple: [Faizon Love, appearedIn, Zookeeper]
  • A. Zookeeper chosen
    Zookeeper is a 2011 comedy film starring Kevin James as a kindhearted animal caretaker who receives romantic advice from talking zoo animals.
  • B. Zoot
    Zoot is a fictional animal character name commonly used in entertainment and media, often evoking a quirky or playful creature.
  • C. Zoot
    Zoot is the nickname of Zoot Sims, an influential American jazz saxophonist known for his swinging style and work in the cool jazz and big band traditions.
  • D. The Zookeeper
    The Zookeeper is a film featuring Czech actor Karel Roden in a prominent role.
  • E. Plottier
    Plottier is a city in the Neuquén Province of Argentina, located in the Patagonian region and known for its agricultural production and proximity to the provincial capital, Neuquén.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e43d8208190aff4f9cf7f2c2a8a completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea547e4819098baf88f3c605242 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.