Triple
T11391083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sévrier |
E269835
|
entity |
| Predicate | intercommunality |
P15149
|
FINISHED |
| Object | CA Grand Annecy |
E214359
|
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: CA Grand Annecy | Statement: [Sévrier, intercommunality, CA Grand Annecy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CA Grand Annecy Context triple: [Sévrier, intercommunality, CA Grand Annecy]
-
A.
TER Lyon–Grenoble
TER Lyon–Grenoble is a regional train service in France that connects the cities of Lyon and Grenoble as part of the TER Auvergne-Rhône-Alpes network.
-
B.
Annecy agglomeration
chosen
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.
-
C.
Annecy
Annecy is a picturesque city in southeastern France, known for its medieval old town, canals, and lakeside setting in the French Alps.
-
D.
Annecy, France
Annecy, France is a picturesque Alpine town in southeastern France known for its medieval old town, canals, and the clear blue waters of Lake Annecy.
-
E.
Élan Chalon
Élan Chalon is a professional French basketball club best known for competing in the country’s top leagues and European competitions.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d800160a1c81909d115bf89fe54a49 |
completed | April 9, 2026, 7:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58c8f5ed88190b9cc55c0a73993ec |
completed | April 20, 2026, 2:16 a.m. |
Created at: April 8, 2026, 9:34 p.m.