Triple

T23505388
Position Surface form Disambiguated ID Type / Status
Subject Puma language E572266 entity
Predicate hasAlternativeName P39 FINISHED
Object Puma
Puma is a Kiranti language spoken primarily in eastern Nepal by the Puma ethnic community.
 E1589120 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: Puma | Statement: [Puma language, hasAlternativeName, Puma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Puma
Context triple: [Puma language, hasAlternativeName, Puma]
  • A. Puma
    Puma is a major German sportswear and athletic footwear brand known for its performance-oriented shoes, apparel, and collaborations with high-profile athletes and designers.
  • B. Puma
    Puma is a genus of large, slender wild cats best known for the cougar (also called mountain lion or puma), a powerful and adaptable predator found across the Americas.
  • C. Puma
    Puma is the NATO reporting name for the Aérospatiale SA 330J, a medium-lift, twin-engine military transport helicopter used by various armed forces worldwide.
  • D. Puma
    Puma is the codename for Mac OS X 10.1, an early version of Apple’s Mac operating system that improved performance and usability over the initial Mac OS X release.
  • E. PUMA
    PUMA is a physics experiment that studies the properties and interactions of antiprotons at CERN’s Extra Low ENergy Antiproton ring (ELENA).
  • 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: Puma
Triple: [Puma language, hasAlternativeName, Puma]
Generated description
Puma is a Kiranti language spoken primarily in eastern Nepal by the Puma ethnic community.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Puma
Target entity description: Puma is a Kiranti language spoken primarily in eastern Nepal by the Puma ethnic community.
  • A. Puma
    Puma is a major German sportswear and athletic footwear brand known for its performance-oriented shoes, apparel, and collaborations with high-profile athletes and designers.
  • B. Puma
    Puma is a genus of large, slender wild cats best known for the cougar (also called mountain lion or puma), a powerful and adaptable predator found across the Americas.
  • C. Puma
    Puma is the codename for Mac OS X 10.1, an early version of Apple’s Mac operating system that improved performance and usability over the initial Mac OS X release.
  • D. Puma
    Puma is the NATO reporting name for the Aérospatiale SA 330J, a medium-lift, twin-engine military transport helicopter used by various armed forces worldwide.
  • E. PUMA
    PUMA is a physics experiment that studies the properties and interactions of antiprotons at CERN’s Extra Low ENergy Antiproton ring (ELENA).
  • 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_69e245b5e4208190bac8a6509867e394 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a8ff97c88190a67f787e1674619e completed April 29, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0c8277b97481909b1405fd7469b910 completed May 19, 2026, 3:32 p.m.
NEDg Description generation batch_6a0ca6f2d4288190b0b5fd46d2a387bf completed May 19, 2026, 6:07 p.m.
NED2 Entity disambiguation (via description) batch_6a0ca7f09af48190b7bfdae25d2f286b completed May 19, 2026, 6:12 p.m.
Created at: April 17, 2026, 6:07 p.m.