Triple
T7783318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zug |
E187177
|
entity |
| Predicate | distanceToZürich |
P55050
|
FINISHED |
| Object | about 23 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: about 23 kilometres | Statement: [Zug, distanceToZürich, about 23 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToZürich Context triple: [Zug, distanceToZürich, about 23 kilometres]
-
A.
distanceToZurich_km
chosen
Indicates the physical distance, measured in kilometers, between an entity’s location and the city of Zurich.
-
B.
distanceToGeneva
Indicates the spatial distance between a given entity and the location of Geneva.
-
C.
distanceToBasel_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Basel.
-
D.
distanceToBern_km
Indicates the distance, measured in kilometers, between an entity’s location and the city of Bern.
-
E.
distanceFromStrasbourg
Indicates the spatial distance between a given place or entity and the city of Strasbourg.
- 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_69ca82af2d2c8190963861f5e0b8bf21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cae7e779ec8190b77296d9c2ac3210 |
completed | March 30, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69caa488532c819093ac40bba0b3c7ef |
completed | March 30, 2026, 4:27 p.m. |
Created at: March 30, 2026, 4:22 p.m.