Triple
T6035121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tilburg |
E134398
|
entity |
| Predicate | distanceToBredaKmApproximate |
P68891
|
FINISHED |
| Object | 23 |
—
|
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: 23 | Statement: [Tilburg, distanceToBredaKmApproximate, 23]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBredaKmApproximate Context triple: [Tilburg, distanceToBredaKmApproximate, 23]
-
A.
cityDistanceFromBrussels_km
Indicates the distance, measured in kilometers, between a given city and Brussels.
-
B.
distanceToAmsterdamCentraal
Indicates the physical distance between a given location and Amsterdam Centraal station.
-
C.
distanceToGroningenCity_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Groningen.
-
D.
roadDistanceToUtrecht_km
Indicates the distance in kilometers between an entity and Utrecht when traveling by road.
-
E.
distanceToBudapest_km
Indicates the physical distance, measured in kilometers, between a given location and Budapest.
- 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b33a7c8190ad6282286199b192 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.