Triple

T17605097
Position Surface form Disambiguated ID Type / Status
Subject Thomas Muir E428808 entity
Predicate workLocation P7 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: [Thomas Muir, workLocation, Cape Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cape Town
Context triple: [Thomas Muir, workLocation, 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. 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.
  • E. Port Elizabeth
    Port Elizabeth is the main town and harbor on the Caribbean island of Bequia in Saint Vincent and the Grenadines, known for its yachting, beaches, and relaxed island atmosphere.
  • 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_69d889e1c6148190ba76241e74688f8b completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46c4b4ee88190827ea28b99ca6f33 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.