Triple
T1573947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavalaire-sur-Mer |
E33604
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Saint-Tropez |
E64451
|
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: Saint-Tropez | Statement: [Cavalaire-sur-Mer, near, Saint-Tropez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Tropez Context triple: [Cavalaire-sur-Mer, near, Saint-Tropez]
-
A.
Saint-Tropez
chosen
Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
-
B.
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.
-
C.
Le Cannet
Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
-
D.
City of Nice
The City of Nice is a major coastal city on the French Riviera, renowned for its Mediterranean climate, historic old town, and rich artistic and cultural heritage.
-
E.
Saintes-Maries-de-la-Mer
Saintes-Maries-de-la-Mer is a coastal town in southern France known as a pilgrimage site and seaside resort at the edge of the Camargue wetlands.
- 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_69a885f27a4c8190a4622252cdf54c00 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a908bcd87881908b911314a30dd327 |
completed | March 5, 2026, 4:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb90e16081908d70df182b7efb8a |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 4, 2026, 7:27 p.m.