Triple
T8572031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Selzach |
E202947
|
entity |
| Predicate | distanceToJuraMountains |
P83702
|
FINISHED |
| Object | located at the foot of the Jura Mountains |
—
|
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: located at the foot of the Jura Mountains | Statement: [Selzach, distanceToJuraMountains, located at the foot of the Jura Mountains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToJuraMountains Context triple: [Selzach, distanceToJuraMountains, located at the foot of the Jura Mountains]
-
A.
distanceToAlps
Indicates the spatial distance between a given location or entity and the Alps.
-
B.
distanceToPyrenees
Indicates the spatial distance between a given location or entity and the Pyrenees.
-
C.
distanceToZurich_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Zurich.
-
D.
distanceToGeneva
Indicates the spatial distance between a given entity and the location of Geneva.
-
E.
distanceToBern_km
Indicates the distance, measured in kilometers, between an entity’s location and the city of Bern.
- 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_69ca8327b0a881908606ff860713964d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbea43843c8190ac2224d427bb7a75 |
completed | March 31, 2026, 3:37 p.m. |
| PD | Predicate disambiguation | batch_69cbd11856048190a1ce4b83a38f6965 |
completed | March 31, 2026, 1:50 p.m. |
| PDg | Predicate description generation | batch_69cbe30e37ac8190b685df36274602b5 |
completed | March 31, 2026, 3:06 p.m. |
Created at: March 30, 2026, 6:21 p.m.