Triple

T2622334
Position Surface form Disambiguated ID Type / Status
Subject Festival of the Lion King E59035 entity
Predicate featuresHosts P42287 FINISHED
Object Kibibi
Kibibi is a lively and energetic host character in Disney's "Festival of the Lion King" stage show at Disney theme parks.
E283318 NE FINISHED

How this triple was built (4 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: Kibibi | Statement: [Festival of the Lion King, featuresHosts, Kibibi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kibibi
Context triple: [Festival of the Lion King, featuresHosts, Kibibi]
  • A. Kabiye
    Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
  • B. Kubban
    Kubban is an ancient Egyptian locality known as the cult center of the regional form of the god Horus, referred to as Horus of Kubban.
  • C. Jebba
    Jebba is a town in western Nigeria known for its strategic location on the Niger River and its historic bridge linking northern and southern Nigeria.
  • D. Bisha
    Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
  • E. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kibibi
Triple: [Festival of the Lion King, featuresHosts, Kibibi]
Generated description
Kibibi is a lively and energetic host character in Disney's "Festival of the Lion King" stage show at Disney theme parks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kibibi
Target entity description: Kibibi is a lively and energetic host character in Disney's "Festival of the Lion King" stage show at Disney theme parks.
  • A. Kabiye
    Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
  • B. Kubban
    Kubban is an ancient Egyptian locality known as the cult center of the regional form of the god Horus, referred to as Horus of Kubban.
  • C. Jebba
    Jebba is a town in western Nigeria known for its strategic location on the Niger River and its historic bridge linking northern and southern Nigeria.
  • D. Bisha
    Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
  • E. Kibushi
    Kibushi is a Bantu language spoken primarily in Mayotte, where it serves as one of the island’s main regional languages.
  • F. None of above. chosen

Provenance (5 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abdd1ca0248190aa15f80b2798524e completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69af909918b88190905df6637ec0e412 completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af91625bd481908d3666af3cd3733f completed March 10, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_69af91f9e1208190aa149c9afc84911c completed March 10, 2026, 3:37 a.m.
Created at: March 6, 2026, 9:50 p.m.