Triple
T24261197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Mongie |
E604706
|
entity |
| Predicate | hasMountainRestaurants |
P155363
|
FINISHED |
| Object | yes |
—
|
LITERAL 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: yes | Statement: [La Mongie, hasMountainRestaurants, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMountainRestaurants Context triple: [La Mongie, hasMountainRestaurants, yes]
-
A.
hasMountainHutsNearby
Indicates that a location or geographic feature has one or more mountain huts situated in its nearby surroundings.
-
B.
hasMountainStation
Indicates that an entity possesses or is associated with a station located in a mountainous area.
-
C.
hasMountainStationFacilities
Indicates that something provides or is equipped with facilities specifically intended for use at a mountain station.
-
D.
mountainHotelIsOneOf
Indicates that something belongs to or is a member of the specified set or category of mountain hotels.
-
E.
hasMountainHotel
Indicates that a location or region contains or is associated with a hotel situated in a mountainous area.
- F. None of above. chosen
Provenance (4 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_69e29544c29c8190b023606eafe5d36a |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28c6727388190862e3ce09c372c70 |
completed | April 29, 2026, 10:55 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f1c6d4e99081909f61899eccafb73e |
completed | April 29, 2026, 8:52 a.m. |
Created at: April 18, 2026, 12:06 a.m.