Triple
T8974806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annecy agglomeration |
E214359
|
entity |
| Predicate | centeredOn |
P164
|
FINISHED |
| Object | Annecy |
E410098
|
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: Annecy | Statement: [Annecy agglomeration, centeredOn, Annecy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annecy Context triple: [Annecy agglomeration, centeredOn, Annecy]
-
A.
Annecy
chosen
Annecy is a picturesque city in southeastern France, known for its medieval old town, canals, and lakeside setting in the French Alps.
-
B.
Thonon-les-Bains
Thonon-les-Bains is a French spa and resort town in the Haute-Savoie region, known for its lakeside setting on Lake Geneva and views of the Alps.
-
C.
Briançon
Briançon is a fortified alpine town in southeastern France, known as one of the highest cities in Europe and a key historical stronghold near the Italian border.
-
D.
Nyons
Nyons is a small town in southeastern France renowned for its olive production and picturesque setting in the Drôme Provençale region.
-
E.
Annecy agglomeration
Annecy agglomeration is an urban area in southeastern France centered on the city of Annecy, known for its lakeside setting, Alpine surroundings, and role as a regional economic and cultural hub.
- 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_69ca839dbf608190a2f5990477115d29 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6784d1808190899c980f76084ff8 |
completed | April 1, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc966f7d881908f4f80c2a0d820fe |
completed | April 3, 2026, 2:06 p.m. |
Created at: March 30, 2026, 7:02 p.m.