Triple
T3035231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voie normale du Goûter |
E82992
|
entity |
| Predicate | startsFrom |
P12530
|
FINISHED |
| Object | Les Houches |
E69658
|
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: Les Houches | Statement: [Voie normale du Goûter, startsFrom, Les Houches]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Houches Context triple: [Voie normale du Goûter, startsFrom, Les Houches]
-
A.
Les Houches
chosen
Les Houches is a French Alpine village and ski resort near Chamonix, known for its family-friendly slopes and World Cup downhill course.
-
B.
Thoiry
Thoiry is a commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
-
C.
Meudon
Meudon is a suburban commune in the southwestern outskirts of Paris, France, known historically as a residential area for artists, intellectuals, and the French elite.
-
D.
Saint-Flour
Saint-Flour is a historic hilltop town in the Cantal department of south-central France, known for its medieval architecture and dramatic setting in the Auvergne region.
-
E.
Grenoble
Grenoble is a major city in southeastern France, known for its Alpine setting, universities, and research centers.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2a40b48190bfa7cdbb0fbd87f8 |
completed | March 8, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dec577d481909a659607c17983ce |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3:01 p.m.