Triple
T3491361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French Riviera |
E73737
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Cagnes-sur-Mer |
E393279
|
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: Cagnes-sur-Mer | Statement: [French Riviera, hasCity, Cagnes-sur-Mer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cagnes-sur-Mer Context triple: [French Riviera, hasCity, Cagnes-sur-Mer]
-
A.
Cagnes-sur-Mer
chosen
Cagnes-sur-Mer is a coastal town on the French Riviera in southeastern France, known for its Mediterranean beaches and historic hilltop village.
-
B.
Le Cannet
Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
-
C.
Antibes
Antibes is a historic resort town on the French Riviera known for its Mediterranean coastline, old town, and association with artists such as Pablo Picasso.
-
D.
Berck-sur-Mer
Berck-sur-Mer is a seaside resort town in northern France known for its sandy beaches, coastal tourism, and traditional fishing heritage.
-
E.
Mandelieu-la-Napoule
Mandelieu-la-Napoule is a coastal resort town on the French Riviera in southeastern France, known for its beaches, marina, and proximity to Cannes.
- 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_69b65082ca248190bfe7350ccc6b6b6a |
completed | March 15, 2026, 6:24 a.m. |
Created at: March 8, 2026, 3:18 p.m.