Triple
T11606996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpilles Regional Natural Park |
E275284
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Mouriès |
E618814
|
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: Mouriès | Statement: [Alpilles Regional Natural Park, containsSettlement, Mouriès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mouriès Context triple: [Alpilles Regional Natural Park, containsSettlement, Mouriès]
-
A.
Mouriès
chosen
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
B.
Malaucène
Malaucène is a picturesque Provençal village in southeastern France, known as a popular base for cyclists and tourists visiting and climbing Mont Ventoux.
-
C.
Roquebillière
Roquebillière is a small commune in southeastern France, situated in the Alpes-Maritimes department in the Provence-Alpes-Côte d’Azur region.
-
D.
Parempuyre
Parempuyre is a commune in southwestern France known for its location near Bordeaux and its role in the Médoc wine-producing region.
-
E.
Aigues-Mortais
Aigues-Mortais are the inhabitants of Aigues-Mortes, a historic fortified town in the Occitanie region of southern France.
- 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_69d6aaf84b548190ac072e4fb89ae18f |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d89551649c81908096ff392677442d |
completed | April 10, 2026, 6:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f28092eb108190be203276e7dfa4b5 |
completed | April 29, 2026, 10:05 p.m. |
Created at: April 8, 2026, 9:38 p.m.