Triple
T1356895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cathays Park |
E29009
|
entity |
| Predicate | adminCenterOf |
P18611
|
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: [Cathays Park, adminCenterOf, Cardiff]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cardiff Context triple: [Cathays Park, adminCenterOf, 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_69a498d77abc8190913bf57e5f51d2c4 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c28db5048190a279ee9882caaeaf |
completed | March 1, 2026, 10:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad607ead308190a599fac02c91e77e |
completed | March 8, 2026, 11:41 a.m. |
Created at: March 1, 2026, 7:56 p.m.