Triple

T15353932
Position Surface form Disambiguated ID Type / Status
Subject Geoffrey Clayton E367122 entity
Predicate basedIn P40 FINISHED
Object Cape Town, South Africa 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, South Africa | Statement: [Geoffrey Clayton, basedIn, Cape Town, South Africa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cape Town, South Africa
Context triple: [Geoffrey Clayton, basedIn, Cape Town, South Africa]
  • 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. Langa, Cape Town, South Africa
    Langa, Cape Town, South Africa is one of Cape Town’s oldest townships, historically significant as a center of Black urban life and culture during and after apartheid.
  • E. Natal, South Africa
    Natal, South Africa was a former British colony and later a province on the country’s eastern coast, centered around the port city of Durban and known for its diverse population and sugarcane agriculture.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2a8e88819093e4b7479b2c80cd completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0319f248190a37c9afa09c32428 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 3:18 a.m.