Triple

T22512663
Position Surface form Disambiguated ID Type / Status
Subject CPT E556558 entity
Predicate associatedAirportCity P2903 FINISHED
Object Cape Town NE NERFINISHED

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: Cape Town | Statement: [CPT, associatedAirportCity, Cape Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cape Town
Context triple: [CPT, associatedAirportCity, Cape Town]
  • A. Cape Town chosen
    Cape Town is a major coastal city in South Africa known for its iconic Table Mountain, diverse culture, and role as the country’s legislative capital.
  • B. Durban
    Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
  • C. Johannesburg
    Johannesburg is a champion Thoroughbred racehorse and successful sire, best known for his unbeaten two-year-old season and victory in the 2001 Breeders’ Cup Juvenile.
  • D. Durban–Cape Town
    Durban–Cape Town is a major domestic air route in South Africa connecting the coastal cities of Durban and Cape Town.
  • E. Port Elizabeth
    Port Elizabeth is a large coastal city in South Africa known for its major seaport, automotive industry, and popular beaches along Algoa Bay.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e555edc81909ca803587dafd747 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15d61a27881909faed490d2b65f39 completed April 29, 2026, 1:22 a.m.
Created at: April 16, 2026, 8:50 p.m.