Triple

T31516660
Position Surface form Disambiguated ID Type / Status
Subject Black Panther: Wakanda Forever – Music From and Inspired By E804088 entity
Predicate featuresArtist P1952 FINISHED
Object Kamo Mphela
Kamo Mphela is a South African singer, dancer, and performer best known for her energetic contributions to the amapiano music scene.
E1967367 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: Kamo Mphela | Statement: [Black Panther: Wakanda Forever – Music From and Inspired By, featuresArtist, Kamo Mphela]
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: Kamo Mphela
Triple: [Black Panther: Wakanda Forever – Music From and Inspired By, featuresArtist, Kamo Mphela]
Generated description
Kamo Mphela is a South African singer, dancer, and performer best known for her energetic contributions to the amapiano music scene.

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_69f348ceb0a48190ae7feca263b6296c completed April 30, 2026, 12:19 p.m.
NER Named-entity recognition batch_69f6a25863648190867b5ad86681fee2 completed May 3, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_6a2b2d7a981c8190a99445fa61cbc80a completed June 11, 2026, 9:49 p.m.
NEDg Description generation batch_6a2b2fb7c10c8190a426374ba7e230fc completed June 11, 2026, 9:59 p.m.
NED2 Entity disambiguation (via description) batch_6a2b310483b0819090147b38cdc00cf8 completed June 11, 2026, 10:04 p.m.
Created at: April 30, 2026, 9:53 p.m.