Triple
T27369050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barendrecht railway station |
E690255
|
entity |
| Predicate | hasNeighbouringStationNorth |
P32736
|
FINISHED |
| Object | Rotterdam Lombardijen railway station |
—
|
NE NERFINISHED |
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: Rotterdam Lombardijen railway station | Statement: [Barendrecht railway station, hasNeighbouringStationNorth, Rotterdam Lombardijen railway station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNeighbouringStationNorth Context triple: [Barendrecht railway station, hasNeighbouringStationNorth, Rotterdam Lombardijen railway station]
-
A.
adjacentStationNorth
chosen
Indicates that one station is directly adjacent to another station to its north.
-
B.
hasAdjacentStationDirectionNorthwest
Indicates that one station is directly adjacent to another in the northwest direction.
-
C.
adjacentStationTowardsSouth
Indicates that one station is directly next to another in the southward direction along a route or line.
-
D.
adjacentStationSouth
Indicates that one station is directly to the south of another station, with no other station in between.
-
E.
adjacentStationWest
Indicates that one station is immediately to the west of another station in a spatial or network layout.
- 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_69ef51ff826081909e42c8e2bfb97941 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 27, 2026, 12:18 p.m.