Triple

T5427545
Position Surface form Disambiguated ID Type / Status
Subject Sir Gaerfyrddin E121398 entity
Predicate borders P224 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: [Sir Gaerfyrddin, borders, Swansea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swansea
Context triple: [Sir Gaerfyrddin, borders, 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. 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.
  • D. Haverfordwest
    Haverfordwest is a historic market town in southwest Wales that serves as the principal commercial and administrative centre of Pembrokeshire.
  • E. Southampton
    Southampton is a wealthy town and popular seaside resort community on the South Fork of Long Island, New York, known for its beaches, historic villages, and part of the Hamptons.
  • 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_69bd463c65f0819082ee6483ab4b466a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd881998308190a071af0fe44997bc completed March 20, 2026, 5:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3abfc7e88190b8f0a31b61c33973 completed March 22, 2026, 12:41 a.m.
Created at: March 20, 2026, 2:06 p.m.