Triple

T3563409
Position Surface form Disambiguated ID Type / Status
Subject Tha Last Meal E75388 entity
Predicate featuresArtist P1952 FINISHED
Object Kokane E399985 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: Kokane | Statement: [Tha Last Meal, featuresArtist, Kokane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kokane
Context triple: [Tha Last Meal, featuresArtist, Kokane]
  • A. Kokane chosen
    Kokane is an American rapper and singer known for his distinctive G-funk style and frequent collaborations with West Coast hip hop artists.
  • B. Hacha-Kekan
    Hacha-Kekan is a traditional cultural festival of the Karbi people that showcases their indigenous rituals, music, dance, and communal celebrations.
  • C. Konedobu
    Konedobu is a suburb of Port Moresby in Papua New Guinea, known for housing many government offices and administrative facilities.
  • D. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • E. Kokona
    Kokona is a local government area in Nasarawa State, Nigeria, serving as an administrative subdivision of the state.
  • 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_69ad85d45090819086f34fb85d850a1e completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0a60e6c8190a3c3ddae5b6ded54 completed March 8, 2026, 6:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5335e1e348190912455cd90009558 completed March 14, 2026, 10:07 a.m.
Created at: March 8, 2026, 3:21 p.m.