Triple
T7201373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argelès-sur-Mer |
E168752
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Collioure |
E71734
|
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: Collioure | Statement: [Argelès-sur-Mer, locatedNear, Collioure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Collioure Context triple: [Argelès-sur-Mer, locatedNear, Collioure]
-
A.
Collioure
chosen
Collioure is a picturesque coastal town in southern France renowned for its vibrant light and colors that inspired Fauvist painters such as Henri Matisse.
-
B.
Leucate
Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
-
C.
Hyères
Hyères is a coastal town in southeastern France known for its Mediterranean climate, historic old town, and nearby Golden Islands (Îles d’Hyères).
-
D.
Sainte-Maxime
Sainte-Maxime is a seaside resort town on the French Riviera known for its Mediterranean beaches, marina, and views across the bay to Saint-Tropez.
-
E.
La Seyne-sur-Mer
La Seyne-sur-Mer is a coastal town in southeastern France on the Mediterranean, historically known for its major shipbuilding industry.
- 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e94971508190bb38184c9af2fe51 |
completed | March 27, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bfb0f4688190a677b818a0b3619c |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:52 p.m.