Triple
T16618231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fawkner railway station |
E403749
|
entity |
| Predicate | hasMykiCardReaders |
P123567
|
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: [Fawkner railway station, hasMykiCardReaders, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMykiCardReaders Context triple: [Fawkner railway station, hasMykiCardReaders, yes]
-
A.
hasOpalCardReaders
Indicates that an entity is equipped with or contains Opal card readers for processing Opal transit card transactions.
-
B.
hasICCardReaders
Indicates that an entity is equipped with or contains IC card reader devices.
-
C.
hasSelfServiceTicketMachines
Indicates that an entity is equipped with self-service ticket machines available for use.
-
D.
cardSlots
Indicates a relationship where specific positions or slots are allocated or available for holding cards.
-
E.
hasRetailKiosks
Indicates that one entity operates or maintains retail kiosks associated with or located within another entity.
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754bc4cc8190a586732fc6507b40 |
completed | April 18, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.