Triple

T15417261
Position Surface form Disambiguated ID Type / Status
Subject Point Seen Money Gone E369274 entity
Predicate producer P490 FINISHED
Object Bongo ByTheWay E1016744 NE FINISHED

How this triple was built (2 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: Bongo ByTheWay | Statement: [Point Seen Money Gone, producer, Bongo ByTheWay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bongo ByTheWay
Context triple: [Point Seen Money Gone, producer, Bongo ByTheWay]
  • A. Bongo ByTheWay chosen
    Bongo ByTheWay is an American record producer and songwriter known for his work in contemporary R&B and hip-hop with prominent artists across the industry.
  • B. Dor Bongo
    Dor Bongo is an alternative name for the Bongo language, a Central Sudanic language spoken primarily in South Sudan.
  • C. Bongo Flava
    Bongo Flava is a popular Tanzanian music genre that blends hip hop, R&B, reggae, and traditional East African sounds, often featuring Swahili lyrics and socially conscious themes.
  • D. Conga
    "Conga" is a 1985 Latin pop-dance hit by Gloria Estefan and Miami Sound Machine that popularized Latin rhythms in mainstream American pop music.
  • E. Bongo
    Bongo is an animated musical segment from Disney’s 1947 anthology film "Fun and Fancy Free," following the adventures of a circus bear who longs for freedom and love.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ea8a8a081909749db1b29d85fcc completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a78f9cc819097a6ff1e0cbdbcf3 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:20 a.m.