Triple
T586191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam Centraal |
E15162
|
entity |
| Predicate | numberOfPlatformTracks |
P843
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [Amsterdam Centraal, numberOfPlatformTracks, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfPlatformTracks Context triple: [Amsterdam Centraal, numberOfPlatformTracks, 15]
-
A.
numberOfTracks
Indicates the quantity of tracks associated with a given entity.
-
B.
hasNumberOfPlatforms
chosen
Indicates the relationship that specifies how many platforms are associated with a given entity.
-
C.
numberOfStations
Indicates the total count of stations associated with or contained by a given entity.
-
D.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an entity.
-
E.
hasTerminatingPlatforms
Indicates that the subject location or facility includes platforms where rail or transit services begin or end their routes, rather than passing through.
- 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_69a4935783b8819082b77726ec10cc42 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49b9a46388190a094b9ebf8dec397 |
completed | March 1, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69a494ca68448190a516b9c3525d8916 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:33 p.m.