Triple
T18793208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blaricum |
E459567
|
entity |
| Predicate | distanceToAmsterdamApprox |
P85383
|
FINISHED |
| Object | about 30 km southeast |
—
|
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 30 km southeast | Statement: [Blaricum, distanceToAmsterdamApprox, about 30 km southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToAmsterdamApprox Context triple: [Blaricum, distanceToAmsterdamApprox, about 30 km southeast]
-
A.
distanceToAmsterdam
chosen
Indicates the spatial distance between a given location and the city of Amsterdam.
-
B.
distanceToRotterdam
Indicates the measured distance between a given entity’s location and the city of Rotterdam.
-
C.
distanceToAmsterdamCentraal
Indicates the physical distance between a given location and Amsterdam Centraal station.
-
D.
distanceToUtrecht
Indicates the spatial distance between a given entity and the location of Utrecht.
-
E.
distanceToEindhovenKmApproximate
Indicates the approximate distance, measured in kilometers, between a given entity and Eindhoven.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59787e5988190883ed575ab4b6dec |
completed | April 20, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e48d16dd34819096e096d0c0e4c15c |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:53 a.m.