Triple

T1748771
Position Surface form Disambiguated ID Type / Status
Subject The Jungle Book (2016 film) E38392 entity
Predicate character P662 FINISHED
Object Bagheera
Bagheera is the wise and protective black panther who mentors and safeguards Mowgli in Disney’s live-action adaptation of The Jungle Book.
E197209 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: Bagheera | Statement: [The Jungle Book (2016 film), character, Bagheera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bagheera
Context triple: [The Jungle Book (2016 film), character, Bagheera]
  • A. Mufasa
    Mufasa is the wise and noble lion king of the Pride Lands and father of Simba in Disney's The Lion King.
  • B. The Tiger
    The Tiger is the costumed feline mascot that represents Princeton University's athletic teams, particularly its football program.
  • C. Leões
    Leões is the popular nickname for Sporting Clube de Portugal, one of Portugal’s biggest football clubs, symbolizing the team’s lion emblem and fighting spirit.
  • D. Lion
    Lion is a 2016 biographical drama film about an Indian boy separated from his family and adopted in Australia who later uses Google Earth to find his way home.
  • E. Lion
    Lion was a prominent warship of the Royal Scots Navy, recognized for its significant role in Scotland’s early modern naval history.
  • 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: Bagheera
Triple: [The Jungle Book (2016 film), character, Bagheera]
Generated description
Bagheera is the wise and protective black panther who mentors and safeguards Mowgli in Disney’s live-action adaptation of The Jungle Book.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bagheera
Target entity description: Bagheera is the wise and protective black panther who mentors and safeguards Mowgli in Disney’s live-action adaptation of The Jungle Book.
  • A. Mufasa
    Mufasa is the wise and noble lion king of the Pride Lands and father of Simba in Disney's The Lion King.
  • B. The Tiger
    The Tiger is the costumed feline mascot that represents Princeton University's athletic teams, particularly its football program.
  • C. Leões
    Leões is the popular nickname for Sporting Clube de Portugal, one of Portugal’s biggest football clubs, symbolizing the team’s lion emblem and fighting spirit.
  • D. Lion
    Lion is a 2016 biographical drama film about an Indian boy separated from his family and adopted in Australia who later uses Google Earth to find his way home.
  • E. Lion
    Lion was a prominent warship of the Royal Scots Navy, recognized for its significant role in Scotland’s early modern naval history.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63ee4d2081909dfd6d3244228c56 completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada0e21e58819082943212bd725581 completed March 8, 2026, 4:16 p.m.
NEDg Description generation batch_69ada1a2fb9481909d9ed587921ca6b6 completed March 8, 2026, 4:19 p.m.
NED2 Entity disambiguation (via description) batch_69ada4dfc9188190845a4e4490318d68 completed March 8, 2026, 4:33 p.m.
Created at: March 4, 2026, 7:31 p.m.