Triple

T19641179
Position Surface form Disambiguated ID Type / Status
Subject Percy Thomas E471542 entity
Predicate workLocation P7 FINISHED
Object Swansea 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: Swansea | Statement: [Percy Thomas, workLocation, Swansea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swansea
Context triple: [Percy Thomas, workLocation, Swansea]
  • A. Swansea chosen
    Swansea is a coastal city in South Wales known for its maritime heritage, industrial history, and role as a target during World War II air raids.
  • B. Swansea
    Swansea is a coastal town in Bristol County, Massachusetts, known for its suburban character and proximity to both Providence and Fall River.
  • C. Swansea
    Swansea is a coastal electoral district in the New South Wales Legislative Assembly, centered around the Lake Macquarie and Swansea Channel region of Australia.
  • D. Swansea West
    Swansea West is a UK parliamentary constituency in the city of Swansea, Wales, represented in the House of Commons.
  • E. Cardiff
    Cardiff is the capital and largest city of Wales, known as a major cultural, commercial, and sporting center with a rich industrial and maritime history.
  • 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_69d8e511f28481909f4bc3ea9191e54a completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e6412224d481909524d7654a36d49b completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:44 p.m.