Triple

T6443882
Position Surface form Disambiguated ID Type / Status
Subject Table Mountain National Park E138291 entity
Predicate hasViewOf P854 FINISHED
Object City of Cape Town E24410 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: City of Cape Town | Statement: [Table Mountain National Park, hasViewOf, City of Cape Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Cape Town
Context triple: [Table Mountain National Park, hasViewOf, City of 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. Hub City
    Hub City is the nickname for Hagerstown, Maryland, reflecting its historical role as a major regional transportation and commercial center.
  • C. Hub City
    Hub City is a common nickname for Moncton, a major transportation and commercial center in New Brunswick, Canada.
  • D. Hub City
    Hub City is the nickname of Crestview, Florida, reflecting its role as a central crossroads and regional center in the Florida Panhandle.
  • E. Muizenberg
    Muizenberg is a seaside suburb of Cape Town, South Africa, known for its popular surfing beach and colorful Victorian beach huts.
  • 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_69c008aa61ac8190bc96715ed79fe2d8 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0698c17ec81909f6bbcbe636a67fd completed March 22, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bc718dc8190b186d09a17562d26 completed March 27, 2026, 9:20 a.m.
Created at: March 22, 2026, 4:46 p.m.