Triple
T10742586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palau Reial |
E253363
|
entity |
| Predicate | hasAutomaticFareGates |
P1973
|
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: [Palau Reial, hasAutomaticFareGates, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomaticFareGates Context triple: [Palau Reial, hasAutomaticFareGates, yes]
-
A.
hasAutomaticFareCollection
Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
-
B.
hasFaregates
chosen
Indicates that an entity is equipped with or contains faregates used to control or validate access, typically for paid entry.
-
C.
hasFareGateConnectionTo
Indicates that there is a direct passage or connection between two areas that is controlled or mediated by fare gates.
-
D.
hasFareZoneSystem
Indicates that an entity uses or is associated with a particular fare zone system for determining travel costs or ticketing.
-
E.
hasFareControlIntegrationSince
Indicates that a fare control system has been integrated with another system or entity starting from a specific point in time.
- 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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710456ec88190ad8aff8804d13aa9 |
completed | April 9, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69d6f30df9948190ab3cdc33977fac14 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:15 p.m.