Triple

T11796570
Position Surface form Disambiguated ID Type / Status
Subject West Africans E280517 entity
Predicate hasDance P24698 FINISHED
Object azonto
Azonto is a popular Ghanaian street dance and music style characterized by energetic, expressive body movements and mimed gestures that often humorously depict everyday activities.
 E947832 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: azonto | Statement: [West Africans, hasDance, azonto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: azonto
Context triple: [West Africans, hasDance, azonto]
  • A. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • B. ANTO
    ANTO is the London Stock Exchange ticker symbol for Antofagasta plc, a major Chilean-based copper mining company.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. andon
    Andon is a visual and auditory alert system used in lean manufacturing to signal production status and highlight problems so they can be addressed immediately.
  • E. AZO
    AZO is the stock ticker symbol for AutoZone, a major American retailer and distributor of automotive replacement parts and accessories.
  • 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: azonto
Triple: [West Africans, hasDance, azonto]
Generated description
Azonto is a popular Ghanaian street dance and music style characterized by energetic, expressive body movements and mimed gestures that often humorously depict everyday activities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: azonto
Target entity description: Azonto is a popular Ghanaian street dance and music style characterized by energetic, expressive body movements and mimed gestures that often humorously depict everyday activities.
  • A. ZAZ
    ZAZ is the IATA airport code for Zaragoza Airport, a major civilian and military airfield serving the city of Zaragoza in northeastern Spain.
  • B. ANTO
    ANTO is the London Stock Exchange ticker symbol for Antofagasta plc, a major Chilean-based copper mining company.
  • C. ZA
    ZA is the ISO 3166-1 alpha-2 country code for South Africa.
  • D. andon
    Andon is a visual and auditory alert system used in lean manufacturing to signal production status and highlight problems so they can be addressed immediately.
  • E. AZO
    AZO is the stock ticker symbol for AutoZone, a major American retailer and distributor of automotive replacement parts and accessories.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a1cda0819092d66a82fd882786 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131110aa081909aa0b0d532e473a5 completed April 28, 2026, 10:13 p.m.
NEDg Description generation batch_69f14e879aa88190a95f13e23dd346f4 completed April 29, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_69f156fa5cc48190a43c1d2e5df346fe completed April 29, 2026, 12:55 a.m.
Created at: April 8, 2026, 9:42 p.m.