Triple

T490854
Position Surface form Disambiguated ID Type / Status
Subject Wales E9984 entity
Predicate hasCity P316 FINISHED
Object Swansea E19285 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: Swansea | Statement: [Wales, hasCity, Swansea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swansea
Context triple: [Wales, hasCity, 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. 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.
  • C. Southampton
    Southampton is a major port city on England’s south coast, historically significant for its maritime trade, shipbuilding, and role as a departure point for transatlantic voyages.
  • D. Bristol
    Bristol is a historic port city in southwest England known for its maritime heritage, vibrant cultural scene, and distinctive Georgian and Victorian architecture.
  • E. Bridgend
    Bridgend is a town and county borough in South Wales, situated roughly midway between Cardiff and Swansea and known historically for its market and industrial heritage.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0e22a308190b04d12974fd08a38 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ab1982f48190b7d7300f0ab9c637 completed March 1, 2026, 9:09 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.