Triple
T14686840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holsworthy railway station |
E344928
|
entity |
| Predicate | hasOpalTopUpMachines |
P49831
|
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: [Holsworthy railway station, hasOpalTopUpMachines, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpalTopUpMachines Context triple: [Holsworthy railway station, hasOpalTopUpMachines, yes]
-
A.
hasSelfServiceTicketMachines
chosen
Indicates that an entity is equipped with self-service ticket machines available for use.
-
B.
hasOpalCardTopUp
Indicates that an entity has performed or received a monetary top-up on an Opal card.
-
C.
hasVIPTerminal
Indicates that one entity possesses or provides access to a VIP (very important person) terminal associated with another entity.
-
D.
hasATMNetwork
Indicates that an entity operates, participates in, or is connected to a particular automated teller machine (ATM) network for financial transactions.
-
E.
hasRetailKiosks
Indicates that one entity operates or maintains retail kiosks associated with or located within another entity.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb58306548190b981956a83a84b95 |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de6579fb7881909becc8f5822b39d4 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.