Triple

T538541
Position Surface form Disambiguated ID Type / Status
Subject Table Bay E12378 entity
Predicate viewOf P854 FINISHED
Object Cape Town skyline 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: Cape Town skyline | Statement: [Table Bay, viewOf, Cape Town skyline]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cape Town skyline
Context triple: [Table Bay, viewOf, Cape Town skyline]
  • 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. Johannesburg, South Africa
    Johannesburg, South Africa is the country’s largest city and economic hub, known for its role in the gold mining industry and as a major urban center in Gauteng province.
  • C. Pretoria, South Africa
    Pretoria, South Africa is one of the country’s three capital cities, serving as the administrative capital and a major center for government, education, and culture.
  • D. Durban
    Durban is a major coastal city in South Africa known for its busy port, subtropical climate, and significant Indian community.
  • E. Mossel Bay
    Mossel Bay is a coastal town and popular tourist destination on South Africa’s Garden Route, known for its beaches, mild climate, and maritime history.
  • 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_69a4933208e88190891f5debab1b776d completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a496dd31c88190b3114805aa31931c completed March 1, 2026, 7:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4e3f3f4e08190a625ae085868b191 completed March 2, 2026, 1:12 a.m.
Created at: March 1, 2026, 7:32 p.m.