Triple

T2625389
Position Surface form Disambiguated ID Type / Status
Subject North Wales E59105 entity
Predicate contains P35 FINISHED
Object Denbighshire E53434 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: Denbighshire | Statement: [North Wales, contains, Denbighshire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denbighshire
Context triple: [North Wales, contains, Denbighshire]
  • A. Denbighshire chosen
    Denbighshire is a historic and principal county in north-east Wales, known for its rural landscapes, market towns, and sections of the Clwydian Range and Dee Valley Area of Outstanding Natural Beauty.
  • B. Merionethshire
    Merionethshire is a historic county in northwest Wales known for its rugged mountainous landscapes and rural character.
  • C. Montgomeryshire
    Montgomeryshire is a historic county and former parliamentary constituency in mid-Wales, known for its rural landscape and market towns such as Newtown and Welshpool.
  • D. Radnorshire
    Radnorshire is a historic county in mid-Wales known for its rural landscapes, small market towns, and incorporation into the modern county of Powys.
  • E. Powys
    Powys is a large, predominantly rural county in mid-Wales known for its mountainous landscapes, market towns, and extensive agricultural areas.
  • 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_69ab4ac558388190962492cd2e1b0ce6 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8b061a08190b7a8459851abaae2 completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69bf185542508190ad71b753bda5d1a3 completed March 21, 2026, 10:14 p.m.
Created at: March 6, 2026, 9:50 p.m.