Triple
T31604546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Tour-de-Trême |
E806443
|
entity |
| Predicate | hasNearbyTouristRegion |
P3449
|
FINISHED |
| Object | Gruyères |
—
|
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: Gruyères | Statement: [La Tour-de-Trême, hasNearbyTouristRegion, Gruyères]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyTouristRegion Context triple: [La Tour-de-Trême, hasNearbyTouristRegion, Gruyères]
-
A.
connectsToTouristRegion
Indicates that one entity has a direct linkage or association to a tourist region, such as through location, access, or service provision.
-
B.
containsTouristArea
Indicates that a place or region includes within its boundaries an area primarily designated or recognized for tourism activities.
-
C.
hasNearbyGeographicalArea
Indicates that one geographical area is located in close spatial proximity to another geographical area.
-
D.
hasRegionalCenterNearby
Indicates that a regional center is located in close proximity to the referenced entity.
-
E.
hasAttractionNearby
chosen
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
- F. None of above.
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_69f348d54ccc8190a03b5df9a2b40b25 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: April 30, 2026, 10:34 p.m.