Triple
T5268422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llangennith |
E119195
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Swansea |
E19285
|
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: Swansea | Statement: [Llangennith, locatedIn, Swansea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swansea Context triple: [Llangennith, locatedIn, Swansea]
-
A.
Swansea
chosen
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.
-
B.
Swansea
Swansea is a coastal town in Bristol County, Massachusetts, known for its suburban character and proximity to both Providence and Fall River.
-
C.
Cardiff
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.
-
D.
Haverfordwest
Haverfordwest is a historic market town in southwest Wales that serves as the principal commercial and administrative centre of Pembrokeshire.
-
E.
Southampton
Southampton is a wealthy town and popular seaside resort community on the South Fork of Long Island, New York, known for its beaches, historic villages, and part of the Hamptons.
- 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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7bfc3f288190b128777caaad2275 |
completed | March 20, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69befe924e80819083fbc761900e263c |
completed | March 21, 2026, 8:24 p.m. |
Created at: March 20, 2026, 1:51 p.m.