Triple
T26148398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shepparton railway station |
E659743
|
entity |
| Predicate | hasVLineCoachConnections |
P158033
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Shepparton railway station, hasVLineCoachConnections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVLineCoachConnections Context triple: [Shepparton railway station, hasVLineCoachConnections, yes]
-
A.
hasVLineServices
chosen
Indicates that an entity is served by, or connected to, transportation services operating on a route or line designated as "V".
-
B.
numberOfIntermediateCoaches
Indicates the count of intermediate coaches (cars) that exist between two specified endpoints in a train configuration.
-
C.
hasRERConnectionCorridor
Indicates that there exists a physical corridor connection between entities within the RER (Regional Express Network) system.
-
D.
hasInteroperableLines
Indicates that two or more systems, networks, or components can operate together seamlessly, exchanging and using each other’s outputs without special adaptation.
-
E.
hasTrailConnection
Indicates that one location is connected to another by a traversable trail or path.
- 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_69ee5bc496a88190af7deb7ab5e081de |
completed | April 26, 2026, 6:39 p.m. |
| NER | Named-entity recognition | batch_69f60bea4cc8819080c1785709c275cb |
completed | May 2, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
Created at: April 26, 2026, 8:23 p.m.