Triple

T30009115
Position Surface form Disambiguated ID Type / Status
Subject Havana Brown E762405 entity
Predicate birthName P65 FINISHED
Object Angelique Meunier
Angelique Meunier is an Australian DJ, singer, and songwriter best known by her stage name Havana Brown, under which she gained international fame for her dance and pop music hits.
 E1901956 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: Angelique Meunier | Statement: [Havana Brown, birthName, Angelique Meunier]
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: Angelique Meunier
Triple: [Havana Brown, birthName, Angelique Meunier]
Generated description
Angelique Meunier is an Australian DJ, singer, and songwriter best known by her stage name Havana Brown, under which she gained international fame for her dance and pop music hits.

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_69f2246a47ac81909cf5213053687ffc completed April 29, 2026, 3:31 p.m.
NER Named-entity recognition batch_69f67953f78481909159491aa686c52b completed May 2, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a274c96687481909e1c2fac8a9353c3 completed June 8, 2026, 11:13 p.m.
NEDg Description generation batch_6a274ddf8d688190b480d115456651c3 completed June 8, 2026, 11:18 p.m.
NED2 Entity disambiguation (via description) batch_6a274eb19fd48190a2d38ace0cc22b77 completed June 8, 2026, 11:22 p.m.
Created at: April 29, 2026, 6:43 p.m.