Triple
T4550471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loughor estuary |
E110149
|
entity |
| Predicate | hasNearbyTown |
P3883
|
FINISHED |
| Object | Gorseinon |
E404707
|
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: Gorseinon | Statement: [Loughor estuary, hasNearbyTown, Gorseinon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gorseinon Context triple: [Loughor estuary, hasNearbyTown, Gorseinon]
-
A.
Gorseinon
chosen
Gorseinon is a suburban town in South Wales known for its community amenities and proximity to Swansea.
-
B.
Penryn
Penryn is a historic town and former parliamentary borough in Cornwall, England.
-
C.
Port Talbot
Port Talbot is an industrial town and port in South Wales, best known for its large steelworks and coastal location on Swansea Bay.
-
D.
Ogmore-by-Sea
Ogmore-by-Sea is a coastal village in the Vale of Glamorgan, Wales, known for its sandy beaches, cliffs, and views across the Bristol Channel.
-
E.
Rhos-on-Sea
Rhos-on-Sea is a small seaside resort and coastal community in North Wales known for its promenade, beach, and historic sites.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57f5a0a081909977ccbb8aba633c |
completed | March 20, 2026, 2:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03391b3481909fd41ac03abe5d1b |
completed | March 21, 2026, 2:32 a.m. |
Created at: March 20, 2026, 1:05 p.m.