Triple
T2483027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Bourget |
E55862
|
entity |
| Predicate | locatedNearCity |
P3883
|
FINISHED |
| Object | Aix-les-Bains |
E46643
|
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: Aix-les-Bains | Statement: [Lake Bourget, locatedNearCity, Aix-les-Bains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aix-les-Bains Context triple: [Lake Bourget, locatedNearCity, Aix-les-Bains]
-
A.
Grenoble
Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
-
B.
Clermont-Ferrand
Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
-
C.
Chambéry
chosen
Chambéry is a historic city in southeastern France that served as the political and cultural center of the former Duchy of Savoy.
-
D.
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.
-
E.
Aix-en-Provence
Aix-en-Provence is a historic and picturesque city in southern France, renowned for its Provençal charm, fountains, and as the hometown of painter Paul Cézanne.
- 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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd163378481908b75f2f5de0e89c6 |
completed | March 7, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0fc39f8a48190bddc14920896ad5b |
completed | March 11, 2026, 5:23 a.m. |
Created at: March 6, 2026, 9:45 p.m.