Triple
T7335966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont-Dore |
E169127
|
entity |
| Predicate | hasNaturalFeature |
P1094
|
FINISHED |
| Object | Monts Dore |
E56438
|
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: Monts Dore | Statement: [Mont-Dore, hasNaturalFeature, Monts Dore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monts Dore Context triple: [Mont-Dore, hasNaturalFeature, Monts Dore]
-
A.
Monts Dore
chosen
Monts Dore is a volcanic mountain range in central France known for its ancient stratovolcano, high plateaus, and popular hiking and winter sports areas.
-
B.
Bois du Cazier
Bois du Cazier is a former coal mine in Marcinelle, Belgium, now preserved as a museum and memorial site best known for the 1956 mining disaster that killed 262 miners.
-
C.
Montmorency plateau
The Montmorency plateau is a raised geographic area in the Val-d'Oise department of northern France, known for its suburban communities overlooking the Paris metropolitan region.
-
D.
Mont-Dore
Mont-Dore is a coastal commune and suburb of Nouméa in New Caledonia, known for its mountainous landscapes and residential areas.
-
E.
Mont-Dore
Mont-Dore is a spa and ski resort town in central France’s Massif Central, known for its thermal springs and access to the nearby volcanic landscapes.
- 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_69c68a568a6481908f11e20db7bc8446 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0c38d6c81908a57ef1eea0e4951 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7ef22d6ac819087f05d6e6787509a |
completed | March 28, 2026, 3:09 p.m. |
Created at: March 27, 2026, 3:04 p.m.