Triple
T17868099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nottwil |
E446757
|
entity |
| Predicate | distanceToLucerne |
P129082
|
FINISHED |
| Object | approximately 20 kilometres |
—
|
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: approximately 20 kilometres | Statement: [Nottwil, distanceToLucerne, approximately 20 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLucerne Context triple: [Nottwil, distanceToLucerne, approximately 20 kilometres]
-
A.
distanceToLugano
Indicates the spatial distance between a given entity and the location of Lugano.
-
B.
distanceToLausanne
Indicates the measured distance between a given entity’s location and the city of Lausanne.
-
C.
distanceToZurich_km
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Zurich.
-
D.
distanceToBern_km
Indicates the distance, measured in kilometers, between an entity’s location and the city of Bern.
-
E.
distanceFromZermatt
Indicates the spatial distance between an entity and the location Zermatt.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa0b69081909fba3b42d237b543 |
completed | April 19, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e6d2e88190ad9ef9f8a99f13e6 |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3db7704588190a34a422421152173 |
completed | April 18, 2026, 7:28 p.m. |
Created at: April 10, 2026, 10:17 a.m.