Triple
T446000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penrhyndeudraeth |
E7020
|
entity |
| Predicate | ceremonialCounty |
P2713
|
FINISHED |
| Object | Gwynedd |
E58308
|
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: Gwynedd | Statement: [Penrhyndeudraeth, ceremonialCounty, Gwynedd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gwynedd Context triple: [Penrhyndeudraeth, ceremonialCounty, Gwynedd]
-
A.
Gwynedd
chosen
Gwynedd is a county and preserved lieutenancy area in north-west Wales known for its rugged coastline, mountains including much of Snowdonia, and strong Welsh language and cultural heritage.
-
B.
Caernarfonshire
Caernarfonshire is a historic county in northwest Wales known for its rugged coastline, mountainous landscapes including parts of Snowdonia, and the medieval Caernarfon Castle.
-
C.
Ceredigion
Ceredigion is a coastal county in west Wales known for its rugged Cardigan Bay shoreline, rural landscapes, and Welsh-speaking communities.
-
D.
Merionethshire
Merionethshire is a historic county in northwest Wales known for its rugged mountainous landscapes and rural character.
-
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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef479ec08190a659eead6eb0d4d0 |
completed | Feb. 28, 2026, 1:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a457fd3a7c81908c761497c3ac04a9 |
completed | March 1, 2026, 3:15 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.