Triple

T8431899
Position Surface form Disambiguated ID Type / Status
Subject The Lion Guard E199132 entity
Predicate mainCharacter P1183 FINISHED
Object Ono
Ono is a keen-eyed egret from Disney Junior’s animated series “The Lion Guard,” serving as the team’s observant and intelligent lookout.
 E732775 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: Ono | Statement: [The Lion Guard, mainCharacter, Ono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ono
Context triple: [The Lion Guard, mainCharacter, Ono]
  • A. Ono
    Ono is a Japanese surname borne by various notable individuals across fields such as academia, politics, and the arts.
  • B. Ohno
    Ohno is a Japanese surname borne by various notable individuals across fields such as sports, science, and entertainment.
  • C. Hiromi
    Hiromi is a Japanese jazz composer and virtuoso pianist renowned for her high-energy performances and fusion of jazz, classical, and rock influences.
  • D. Kishi
    Kishi is a Japanese surname borne by various notable figures in politics, arts, and entertainment.
  • E. Rokkō Airando
    Rokkō Airando is a man-made island in Kobe, Japan, known for its residential areas, commercial facilities, and port-related infrastructure.
  • 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: Ono
Triple: [The Lion Guard, mainCharacter, Ono]
Generated description
Ono is a keen-eyed egret from Disney Junior’s animated series “The Lion Guard,” serving as the team’s observant and intelligent lookout.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ono
Target entity description: Ono is a keen-eyed egret from Disney Junior’s animated series “The Lion Guard,” serving as the team’s observant and intelligent lookout.
  • A. Ono
    Ono is a Japanese surname borne by various notable individuals across fields such as academia, politics, and the arts.
  • B. Ohno
    Ohno is a Japanese surname borne by various notable individuals across fields such as sports, science, and entertainment.
  • C. Hiromi
    Hiromi is a Japanese jazz composer and virtuoso pianist renowned for her high-energy performances and fusion of jazz, classical, and rock influences.
  • D. Kishi
    Kishi is a Japanese surname borne by various notable figures in politics, arts, and entertainment.
  • E. Rokkō Airando
    Rokkō Airando is a man-made island in Kobe, Japan, known for its residential areas, commercial facilities, and port-related infrastructure.
  • 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_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.
NEDg Description generation batch_69ce07851c4081909a9468a386035bb2 completed April 2, 2026, 6:07 a.m.
NED2 Entity disambiguation (via description) batch_69ce07ec00248190bb10fee54265c7f9 completed April 2, 2026, 6:08 a.m.
Created at: March 30, 2026, 6:07 p.m.