Triple
T34503521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montabaur railway station |
E885820
|
entity |
| Predicate | isHighSpeedStopOn |
P17789
|
FINISHED |
| Object | Cologne–Frankfurt high-speed railway |
—
|
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: Cologne–Frankfurt high-speed railway | Statement: [Montabaur railway station, isHighSpeedStopOn, Cologne–Frankfurt high-speed railway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHighSpeedStopOn Context triple: [Montabaur railway station, isHighSpeedStopOn, Cologne–Frankfurt high-speed railway]
-
A.
isSmallStop
Indicates that something functions as a minor or less significant stop within a route, sequence, or process.
-
B.
hasStopType
Indicates that a stop or stopping point is classified as having a particular type or category of stop.
-
C.
hasStopArea
Indicates that an entity is associated with or contains a specific stop area, such as a designated location where vehicles stop.
-
D.
isNonStop
Indicates that a service, trip, or process occurs from start to finish without any intermediate stops or interruptions.
-
E.
hasStop
chosen
Indicates that something (such as a route, service, or journey) includes or is associated with a particular stop or stopping point.
- 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_69f349cc0220819081f154c6964f4dc2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7234bcaa48190ac970759d34e254a |
completed | May 3, 2026, 10:28 a.m. |
| PD | Predicate disambiguation | batch_69f72155c48881909bd40b9aa3febd5a |
completed | May 3, 2026, 10:20 a.m. |
Created at: May 1, 2026, 2:01 a.m.