Triple
T25341677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kananook railway station |
E635429
|
entity |
| Predicate | hasMykiCardVendingMachine |
P165306
|
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: [Kananook railway station, hasMykiCardVendingMachine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMykiCardVendingMachine Context triple: [Kananook railway station, hasMykiCardVendingMachine, yes]
-
A.
hasMykiCardReaders
Indicates that an entity is equipped with or contains Myki card readers for processing Myki cards.
-
B.
hasMykiTopUp
Indicates that an entity has performed or received a Myki card balance top-up transaction.
-
C.
hasOpalOrMykiGates
Indicates that a location or facility is equipped with Opal or Myki ticketing gates for access control or fare validation.
-
D.
hasOpalCard
Indicates that an entity possesses or is assigned an Opal card.
-
E.
ticketMachineAccepts
Indicates that a ticket machine receives and recognizes something (such as payment, a card, or a ticket) as valid input.
- F. None of above. chosen
Provenance (4 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_69e75a99bd6481909476115b35b9a8e4 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f658a91ba0819084fbe3dd8a09f7cd |
completed | May 2, 2026, 8:03 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f657f2c8b08190bfeb3173ef78207d |
completed | May 2, 2026, 8 p.m. |
Created at: April 21, 2026, 1:32 p.m.