Triple
T24994829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yarra Trams |
E625539
|
entity |
| Predicate | vehicleTypeOperated |
P1776
|
FINISHED |
| Object | low-floor trams |
—
|
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: low-floor trams | Statement: [Yarra Trams, vehicleTypeOperated, low-floor trams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleTypeOperated Context triple: [Yarra Trams, vehicleTypeOperated, low-floor trams]
-
A.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
vehicleClassServed
Indicates the class or type of vehicle that a service, facility, or operation is designed to accommodate or serve.
-
C.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
D.
vehicleFor
Indicates that one entity serves as the means of transportation or conveyance for another entity.
-
E.
vehicleFamily
Indicates that two vehicles belong to the same family or category based on shared design, platform, or lineage.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44a48bb8c819087ddf6df8c446489 |
completed | May 1, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
Created at: April 18, 2026, 6:04 a.m.