Triple
T16184086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schöneberg municipal railway |
E392753
|
entity |
| Predicate | numberOfStationsOperated |
P1301
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Schöneberg municipal railway, numberOfStationsOperated, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfStationsOperated Context triple: [Schöneberg municipal railway, numberOfStationsOperated, 5]
-
A.
numberOfStations
chosen
Indicates the total count of stations associated with or contained by a given entity.
-
B.
operatedStation
Indicates that one entity managed, ran, or was responsible for the operation of a particular station.
-
C.
operatedBetweenStations
Indicates that an operation, such as a service or route, took place connecting or running between two specified stations.
-
D.
operatedAmong
Indicates that an entity carried out operations or activities within, or in coordination with, a specified group, set, or collection of other entities.
-
E.
oftenOperatedBy
Indicates that an entity is frequently or typically operated, controlled, or run by another entity.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205fc080819097858f36253fef7c |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.