Triple
T3491367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Riviera |
E73737
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Roquebrune-Cap-Martin |
E190762
|
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: Roquebrune-Cap-Martin | Statement: [French Riviera, hasCity, Roquebrune-Cap-Martin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roquebrune-Cap-Martin Context triple: [French Riviera, hasCity, Roquebrune-Cap-Martin]
-
A.
Roquebrune-Cap-Martin
chosen
Roquebrune-Cap-Martin is a picturesque coastal commune on the French Riviera in southeastern France, known for its medieval village, Mediterranean views, and proximity to Monaco.
-
B.
Fréjus
Fréjus is a historic town and seaside resort on the French Riviera in southeastern France, known for its Roman ruins and Mediterranean coastline.
-
C.
Porto-Vecchio
Porto-Vecchio is a popular seaside resort town in southern Corsica, France, known for its picturesque old port, historic citadel, and nearby white-sand beaches.
-
D.
Leucate
Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
-
E.
Frontignan
Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
- 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_69ad85cca8d4819088494e9f3340fab5 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbaa720c8190af47b052cc66c225 |
completed | March 8, 2026, 6:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bbf19808190b42c9feddc2a1030 |
completed | March 13, 2026, 3:59 a.m. |
Created at: March 8, 2026, 3:18 p.m.