Triple

T13653832
Position Surface form Disambiguated ID Type / Status
Subject Robert Gray E326805 entity
Predicate workLocation P7 FINISHED
Object 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: Cape Town | Statement: [Robert Gray, workLocation, Cape Town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cape Town
Context triple: [Robert Gray, 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 (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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc60ace048190a4b92310ba272bd1 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7941b62bc819082ddb1f48497ff3a completed May 3, 2026, 6:29 p.m.
Created at: April 9, 2026, 9:52 p.m.