Triple

T15056117
Position Surface form Disambiguated ID Type / Status
Subject Rafiki's Planet Watch E379495 entity
Predicate namedAfter P63 FINISHED
Object Rafiki E499058 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: Rafiki | Statement: [Rafiki's Planet Watch, namedAfter, Rafiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rafiki
Context triple: [Rafiki's Planet Watch, namedAfter, Rafiki]
  • A. Rafiki chosen
    Rafiki is a wise, mystical mandrill who serves as a spiritual guide and shaman-like figure in Disney’s The Lion King.
  • B. Simba
    Simba is the stage name of Tanzanian singer and songwriter Diamond Platnumz, a leading figure in contemporary Bongo Flava and East African pop music.
  • C. Simba
    Simba is the lion prince who becomes king in Disney's animated film "The Lion King," known for his journey from guilt-ridden exile to courageous leader.
  • D. Shenzi
    Shenzi is a cunning hyena and one of the primary antagonists in Disney's "The Lion King," known for serving as a key henchman to Scar.
  • E. Jobu Tupaki
    Jobu Tupaki is the chaotic, multiverse-hopping alter ego of Joy Wang who serves as the film’s primary antagonist in the sci-fi action movie "Everything Everywhere All at Once."
  • 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_69deda937f788190899d81bbb2084443 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea5c11fb4819086c4b85a8d29ccf7 completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 3:01 a.m.