Triple
T6863929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myki |
E158348
|
entity |
| Predicate | supportsTicketType |
P24486
|
FINISHED |
| Object | Myki Money |
E158348
|
NE 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: Myki Money | Statement: [Myki, supportsTicketType, Myki Money]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Myki Money Context triple: [Myki, supportsTicketType, Myki Money]
-
A.
Myki
chosen
Myki is Melbourne’s contactless smartcard public transport ticketing system used across trains, trams, and buses in Victoria, Australia.
-
B.
Opal card
The Opal card is a reusable, contactless smartcard used to pay for public transport across much of New South Wales, Australia.
-
C.
Kitaca
Kitaca is a rechargeable contactless smart card used primarily for public transportation and electronic payments in Japan’s Hokkaido region.
-
D.
ORCA card
The ORCA card is a reusable, contactless smart card used to pay fares across multiple public transit systems in the Puget Sound region of Washington State.
-
E.
T-Money
T-Money is a television personality and DJ best known for co-hosting the influential hip-hop music video show "Yo! MTV Raps."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68830cdbc8190a8301c7a9d9f651a |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8897cf48190a2f688d21f1f6c1a |
completed | March 27, 2026, 7:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7942be8708190bad44a9966884515 |
completed | March 28, 2026, 8:41 a.m. |
Created at: March 27, 2026, 2:21 p.m.