Triple
T29765257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S2 (Munich S-Bahn) |
E753886
|
entity |
| Predicate | trunkRouteUsage |
P131062
|
FINISHED |
| Object | runs through the central trunk route of the Munich S-Bahn |
—
|
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: runs through the central trunk route of the Munich S-Bahn | Statement: [S2 (Munich S-Bahn), trunkRouteUsage, runs through the central trunk route of the Munich S-Bahn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trunkRouteUsage Context triple: [S2 (Munich S-Bahn), trunkRouteUsage, runs through the central trunk route of the Munich S-Bahn]
-
A.
trunkSegments
Indicates that an object is composed of or associated with specific segments of a trunk (such as a tree trunk or similar elongated main structure).
-
B.
usedRoutes
Indicates that an entity has utilized or traveled along specific routes.
-
C.
currentUseOfRoute
chosen
Indicates that a particular route is presently being used for a specific purpose, activity, or traffic flow.
-
D.
numberOfTrunksApprox
Indicates an approximate count of trunks associated with an entity, rather than an exact number.
-
E.
usageRoute
Indicates the path, method, or channel through which something is used, applied, or accessed.
- 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_69f0ef827ff88190ade56e0b0846b713 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6745b7004819094f819c8cbb1d4ca |
completed | May 2, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 28, 2026, 8:37 p.m.