Triple
T21039066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winschoten railway station |
E518268
|
entity |
| Predicate | distanceToGroningenByRail_km |
P63224
|
FINISHED |
| Object | approximately 34 |
—
|
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 34 | Statement: [Winschoten railway station, distanceToGroningenByRail_km, approximately 34]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToGroningenByRail_km Context triple: [Winschoten railway station, distanceToGroningenByRail_km, approximately 34]
-
A.
distanceToGroningenCity_km
chosen
Indicates the physical distance, measured in kilometers, between a given location and the city of Groningen.
-
B.
distanceToDenHaagCentraal
Indicates the measured distance between a given location and Den Haag Centraal station.
-
C.
distanceToLeidenCentraal
Indicates the spatial distance between a given location and Leiden Centraal station.
-
D.
distanceToAmsterdamCentraal
Indicates the physical distance between a given location and Amsterdam Centraal station.
-
E.
distanceToRotterdam
Indicates the measured distance between a given entity’s location and the city of Rotterdam.
- 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_69e0b50438e08190917e2538bb8bc034 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fcee13b08190a8b3372f6759cd1b |
completed | April 21, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69e5dbf6728881908a2a43a5c8804a2a |
completed | April 20, 2026, 7:55 a.m. |
Created at: April 16, 2026, 2:13 p.m.