Triple
T28846104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Shaanxi Road station |
E728458
|
entity |
| Predicate | hasAutomaticFareCollectionGates |
P85441
|
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: [South Shaanxi Road station, hasAutomaticFareCollectionGates, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomaticFareCollectionGates Context triple: [South Shaanxi Road station, hasAutomaticFareCollectionGates, yes]
-
A.
hasAutomaticFareCollection
chosen
Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
-
B.
hasFaregates
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
C.
hasOpalOrMykiGates
Indicates that a location or facility is equipped with Opal or Myki ticketing gates for access control or fare validation.
-
D.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
-
E.
airTrainFareCollection
Indicates a relationship where fares for an air train service are collected from passengers or through a designated payment system.
- 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_69f0319e8e7c8190b37288c8845b9dbc |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 28, 2026, 6:42 a.m.