Triple

T14818927
Position Surface form Disambiguated ID Type / Status
Subject Muizenberg Beach E348392 entity
Predicate locatedIn P40 FINISHED
Object Muizenberg E265535 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: Muizenberg | Statement: [Muizenberg Beach, locatedIn, Muizenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muizenberg
Context triple: [Muizenberg Beach, locatedIn, Muizenberg]
  • A. Muizenberg chosen
    Muizenberg is a seaside suburb of Cape Town, South Africa, known for its popular surfing beach and colorful Victorian beach huts.
  • B. Rondebosch
    Rondebosch is a leafy, affluent suburb in Cape Town, South Africa, known for its academic character and proximity to major educational institutions.
  • C. Durbanville
    Durbanville is a suburban town in the northern outskirts of Cape Town, South Africa, known for its wine estates and residential character.
  • D. Paarl
    Paarl is a historic town in South Africa renowned for its wine estates, scenic granite rock formations, and role in the development of the Afrikaans language.
  • E. Mitchells Plain
    Mitchells Plain is a large, predominantly residential township in Cape Town, South Africa, known for its dense population, socio-economic challenges, and vibrant community life.
  • 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_69d822eb8f588190bf53445e730a934f completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decfe4cf38819090f25ef045351d5d completed April 14, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff133571008190b7e7867208095b90 completed May 9, 2026, 10:57 a.m.
Created at: April 10, 2026, 1:50 a.m.