Triple
T31795386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Transit Authority |
E811581
|
entity |
| Predicate | publicTransportNetworkBrand |
P142506
|
FINISHED |
| Object | Sydney Buses |
—
|
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: Sydney Buses | Statement: [State Transit Authority, publicTransportNetworkBrand, Sydney Buses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicTransportNetworkBrand Context triple: [State Transit Authority, publicTransportNetworkBrand, Sydney Buses]
-
A.
publicTransportBrand
chosen
Indicates that a public transport service, line, or vehicle operates under or is associated with a specific brand or branding entity.
-
B.
publicTransportNetworkType
Indicates the type or category of public transportation network associated with or used by an entity.
-
C.
commuterRailBrand
Indicates that a commuter rail service operates under or is associated with a specific brand or branding identity.
-
D.
ferryNetworkBrand
Indicates the brand or commercial identity under which a ferry network operates or is marketed.
-
E.
notableTrainBrand
Indicates that an entity is a well-known or significant brand associated with trains or railway services.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
Created at: April 30, 2026, 11:40 p.m.