Triple
T17199379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elfstedentocht route |
E417436
|
entity |
| Predicate | hasCheckpointsIn |
P30109
|
FINISHED |
| Object | each of the eleven cities |
—
|
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: each of the eleven cities | Statement: [Elfstedentocht route, hasCheckpointsIn, each of the eleven cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCheckpointsIn Context triple: [Elfstedentocht route, hasCheckpointsIn, each of the eleven cities]
-
A.
hasCheckpoint
chosen
Indicates that an entity includes, contains, or is associated with one or more intermediate control or verification points within its structure, process, or path.
-
B.
hasCheckpointControl
Indicates that one entity exercises control, management, or authority over a checkpoint associated with another entity.
-
C.
hasCheckpointType
Indicates that a checkpoint is associated with a specific type or category defining its role or characteristics.
-
D.
hadCheckpoint
Indicates that an entity passed through, reached, or was associated with a specific checkpoint at some point in time.
-
E.
hasCheckInCounters
Indicates that an entity is associated with one or more check-in counters used for processing arrivals or registrations.
- 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daddcd08190a82f36c940bf3f7b |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e383141ae0819096acd71683637cbc |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.