Triple

T1339751
Position Surface form Disambiguated ID Type / Status
Subject First Minister of Wales E28437 entity
Predicate residence P75 FINISHED
Object Cardiff E12034 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: Cardiff | Statement: [First Minister of Wales, residence, Cardiff]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cardiff
Context triple: [First Minister of Wales, residence, Cardiff]
  • A. Cardiff chosen
    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.
  • B. Swansea
    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.
  • C. 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.
  • D. Aberystwyth
    Aberystwyth is a historic seaside and university town on the west coast of Wales, known for its promenade, castle ruins, and role as a cultural and administrative center for the region.
  • E. Llantrisant
    Llantrisant is a historic Welsh town known for its medieval heritage and hilltop setting in South Wales.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c21303c881908fef0b32831222fe completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad231f92bc8190be41c30adb022b65 completed March 8, 2026, 7:19 a.m.
Created at: March 1, 2026, 7:56 p.m.