Triple
T3948017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UCI |
E84793
|
entity |
| Predicate | headquartersCity |
P62
|
FINISHED |
| Object | Aigle |
E324473
|
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: Aigle | Statement: [UCI, headquartersCity, Aigle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aigle Context triple: [UCI, headquartersCity, Aigle]
-
A.
Aigle
chosen
Aigle is a historic town in southwestern Switzerland known for its medieval castle and surrounding vineyards in the canton of Vaud.
-
B.
Nid d'Aigle
Nid d'Aigle is a high-altitude railway terminus and popular starting point for mountaineers heading towards Mont Blanc in the French Alps.
-
C.
Fuissé
Fuissé is a renowned wine-producing village in France’s Burgundy region, particularly famous for its Pouilly-Fuissé Chardonnay wines.
-
D.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
E.
Booué
Booué is a small town in central Gabon situated along the Ogooué River, known as a local transport and trading hub in the region.
- 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_69aed934fbfc8190847068e4546de963 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef90f97188190875165e1b5f699e0 |
completed | March 9, 2026, 4:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5339bc5d481909e750873d65fff4c |
completed | March 14, 2026, 10:08 a.m. |
Created at: March 9, 2026, 3:30 p.m.