Triple
T17988435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Col du Tourmalet |
E430301
|
entity |
| Predicate | hasSkiResort |
P1981
|
FINISHED |
| Object | La Mongie |
—
|
NE NERFINISHED |
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: La Mongie | Statement: [Col du Tourmalet, hasSkiResort, La Mongie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Mongie Context triple: [Col du Tourmalet, hasSkiResort, La Mongie]
-
A.
La Mongie
chosen
La Mongie is a French Pyrenean ski resort village known as a gateway to the Pic du Midi de Bigorre and its observatory.
-
B.
Montagnieu
Montagnieu is a commune in the Ain department of eastern France, situated within the historic wine-producing area of Bugey.
-
C.
Mouriès
Mouriès is a village in southern France’s Provence region, known for its olive oil production and location near the Alpilles hills.
-
D.
Mauguio
Mauguio is a commune in southern France near Montpellier, known for its proximity to the Mediterranean coast and its role as a local economic and transport hub.
-
E.
Mauranger
Mauranger is a scenic village area in Vestland county, Norway, known for its fjords, glaciers, and dramatic mountain landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29d3ad4819096c2600aa2a99f21 |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:23 a.m.