Triple
T893225
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swansea |
E19285
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Pau |
E49264
|
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: Pau | Statement: [Swansea, hasTwinTown, Pau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pau Context triple: [Swansea, hasTwinTown, Pau]
-
A.
Pau
chosen
Pau is a historic city in southwestern France, known as the capital of the Pyrénées-Atlantiques department and for its scenic location near the Pyrenees mountains.
-
B.
Toulouse
Toulouse is a major city in southwestern France known for its aerospace industry, historic pink-brick architecture, and vibrant university and cultural life.
-
C.
Bordeaux
Bordeaux is a renowned wine-producing region in southwestern France, famous for its prestigious red blends and long winemaking tradition.
-
D.
Blaye
Blaye is a wine-producing area on the right bank of the Gironde estuary in southwestern France, known for its red and white Bordeaux wines and historic citadel.
-
E.
Tarbes
Tarbes is a historic city in southwestern France, serving as the capital of the Hautes-Pyrénées department at the foot of the Pyrenees.
- 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_69a4939d37188190848be3d426ebc9ae |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ad212cd8819091eb1b7d606f5afd |
completed | March 1, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a9339ba2e48190872fd771386ba321 |
completed | March 5, 2026, 7:41 a.m. |
Created at: March 1, 2026, 7:39 p.m.