Triple
T31605556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vuissens |
E806473
|
entity |
| Predicate | nearestLargerCenter |
P151188
|
FINISHED |
| Object | Estavayer-le-Lac |
—
|
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: Estavayer-le-Lac | Statement: [Vuissens, nearestLargerCenter, Estavayer-le-Lac]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestLargerCenter Context triple: [Vuissens, nearestLargerCenter, Estavayer-le-Lac]
-
A.
nearestMajorCenter
Indicates that one location is the closest significant urban or population center relative to another location.
-
B.
nearestTownCenter
Indicates that one location is the closest town center to another specified point or area.
-
C.
nearestArea
Indicates that one area is the closest in distance to a given reference point or region compared to all other candidate areas.
-
D.
nearestMajorNeighbor
Indicates that one entity is the closest significant or major neighboring entity to another in terms of spatial proximity.
-
E.
largerNear
chosen
Indicates that one entity is both larger in size than another entity and located in close spatial proximity to it.
- 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_69f71422adac8190a5ceb32dcf820833 |
completed | May 3, 2026, 9:23 a.m. |
| PD | Predicate disambiguation | batch_69f712764d2c819081b64b27e5de4a13 |
completed | May 3, 2026, 9:16 a.m. |
Created at: April 30, 2026, 10:34 p.m.