Triple
T23602175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Potsdam–Brandenburg an der Havel section |
E582787
|
entity |
| Predicate | onMainRoute |
P125679
|
FINISHED |
| Object | Berlin–Magdeburg route |
—
|
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: Berlin–Magdeburg route | Statement: [Potsdam–Brandenburg an der Havel section, onMainRoute, Berlin–Magdeburg route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: onMainRoute Context triple: [Potsdam–Brandenburg an der Havel section, onMainRoute, Berlin–Magdeburg route]
-
A.
mainRouteTerminus
Indicates that a location serves as a primary endpoint or terminus for a given route.
-
B.
mainEntranceOn
Indicates that the primary entrance of one entity is located on or faces toward another entity, such as a particular side, street, or boundary.
-
C.
isRouteOn
chosen
Indicates that one route is located on, follows along, or is aligned with another specified path or infrastructure.
-
D.
isMajorRouteFor
Indicates that something serves as a primary or heavily used pathway or channel for the movement or flow of something else.
-
E.
exampleRoute
Indicates a route that serves as a representative or illustrative path among possible routes between locations.
- 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_69e248faa2788190abb1581742daa6aa |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b0947bd8819097e26643dc257dc0 |
completed | April 29, 2026, 7:17 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:43 p.m.