Triple

T17607430
Position Surface form Disambiguated ID Type / Status
Subject South Wales rail network E428870 entity
Predicate serves P98 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: [South Wales rail network, serves, Swansea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Swansea
Context triple: [South Wales rail network, serves, 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. Cardiff
    Cardiff is an unincorporated community and census-designated place within Egg Harbor Township in Atlantic County, New Jersey, known primarily as a suburban residential area with local commercial development.
  • E. Haverfordwest
    Haverfordwest is a historic market town in southwest Wales that serves as the principal commercial and administrative centre of Pembrokeshire.
  • 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_69e46c4ccef08190aeaa88670364bd74 completed April 19, 2026, 5:46 a.m.
Created at: April 10, 2026, 5:51 a.m.