Triple

T9853046
Position Surface form Disambiguated ID Type / Status
Subject Soca E239515 entity
Predicate relatedGenre P8654 FINISHED
Object Kompa
Kompa is a popular Haitian dance music genre known for its smooth, guitar-driven rhythms and strong influence on Caribbean and diasporic music styles.
E825025 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: Kompa | Statement: [Soca, relatedGenre, Kompa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kompa
Context triple: [Soca, relatedGenre, Kompa]
  • A. Matra
    Matra is a French engineering and aerospace company known for its work in transportation systems, defense, and automotive technologies.
  • B. Fuso
    Fuso is a commercial vehicle manufacturer best known for its trucks and buses, operating as part of Daimler’s global automotive group.
  • C. Citura
    Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
  • D. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • E. Takara
    Takara is a Japanese toy company best known for creating and producing Transformers and other popular action figures.
  • 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: Kompa
Triple: [Soca, relatedGenre, Kompa]
Generated description
Kompa is a popular Haitian dance music genre known for its smooth, guitar-driven rhythms and strong influence on Caribbean and diasporic music styles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kompa
Target entity description: Kompa is a popular Haitian dance music genre known for its smooth, guitar-driven rhythms and strong influence on Caribbean and diasporic music styles.
  • A. Matra
    Matra is a French engineering and aerospace company known for its work in transportation systems, defense, and automotive technologies.
  • B. Fuso
    Fuso is a commercial vehicle manufacturer best known for its trucks and buses, operating as part of Daimler’s global automotive group.
  • C. Citura
    Citura is the public transport operator responsible for managing Reims’ urban transit network, including its tramway system, in northeastern France.
  • D. Mibuchi
    Mibuchi is a Japanese surname borne by individuals such as Tadahiko Mibuchi.
  • E. Takara
    Takara is a Japanese toy company best known for creating and producing Transformers and other popular action figures.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb376d32c819089381cf6ed83629d completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5ee190c8190957451d8d8291df3 completed April 5, 2026, 3:24 a.m.
NEDg Description generation batch_69d1d6a385ac8190b5dd11adfbb7578d completed April 5, 2026, 3:27 a.m.
NED2 Entity disambiguation (via description) batch_69d1d75210f4819096ee05a8b870581e completed April 5, 2026, 3:30 a.m.
Created at: March 30, 2026, 8:34 p.m.