Triple

T8431903
Position Surface form Disambiguated ID Type / Status
Subject The Lion Guard E199132 entity
Predicate featuresCharacter P626 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: [The Lion Guard, featuresCharacter, Rafiki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rafiki
Context triple: [The Lion Guard, featuresCharacter, 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 lion prince who becomes king in Disney's animated film "The Lion King," known for his journey from guilt-ridden exile to courageous leader.
  • C. 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.
  • 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_69ca8313c99081909a5c6d83b91de5b3 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbd1a4876c81908d5a708bb1f35683 completed March 31, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce038902308190bff57c9ce14e72ed completed April 2, 2026, 5:50 a.m.
Created at: March 30, 2026, 6:07 p.m.