Triple
T964033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Usk |
E20796
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Monmouthshire |
E27493
|
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: Monmouthshire | Statement: [Usk, locatedIn, Monmouthshire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monmouthshire Context triple: [Usk, locatedIn, Monmouthshire]
-
A.
Monmouthshire
chosen
Monmouthshire is a historic county and principal area in southeast Wales, known for its rural landscapes, market towns, and rich medieval heritage.
-
B.
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.
-
C.
Denbighshire
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.
-
D.
Pembrokeshire
Pembrokeshire is a coastal county in southwest Wales renowned for its rugged cliffs, sandy beaches, and the Pembrokeshire Coast National Park.
-
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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b4303e5881909d101d11f9732c75 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad1c8c828481909013039009446dc0 |
completed | March 8, 2026, 6:51 a.m. |
Created at: March 1, 2026, 7:40 p.m.