Triple
T4914107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serre-Ponçon Dam |
E110305
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Savines-le-Lac |
E462775
|
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: Savines-le-Lac | Statement: [Serre-Ponçon Dam, locatedNear, Savines-le-Lac]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Savines-le-Lac Context triple: [Serre-Ponçon Dam, locatedNear, Savines-le-Lac]
-
A.
Savines-le-Lac
chosen
Savines-le-Lac is a French Alpine village in the Hautes-Alpes department, known as a lakeside resort on the shores of the Lac de Serre-Ponçon.
-
B.
Lac Chambon
Lac Chambon is a volcanic-origin lake in the Monts Dore massif of central France, known for its scenic mountain setting and recreational activities.
-
C.
Veyrier-du-Lac
Veyrier-du-Lac is a picturesque commune in southeastern France, nestled on the eastern shore of Lake Annecy at the foot of the Alps.
-
D.
Vaujours
Vaujours is a small suburban commune in the northeastern outskirts of Paris, France.
-
E.
Annecy
Annecy is a picturesque city in southeastern France, known for its medieval old town, canals, and lakeside setting in the French Alps.
- 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_69bd44132b94819088522d92beaadc78 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e9f12b48190b3cb5378958d03cd |
completed | March 20, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be77a1ef488190ac9cc34e67a8b243 |
completed | March 21, 2026, 10:49 a.m. |
Created at: March 20, 2026, 1:29 p.m.