Triple
T22749531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R179 |
E562655
|
entity |
| Predicate | usesAutomaticTrainControlInterfaces |
P112656
|
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: [R179, usesAutomaticTrainControlInterfaces, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAutomaticTrainControlInterfaces Context triple: [R179, usesAutomaticTrainControlInterfaces, yes]
-
A.
hasAutomaticTrainControlCompatibility
Indicates that an entity is compatible with, or supports integration with, an automatic train control (ATC) system.
-
B.
hasAutomaticTrainControl
chosen
Indicates that an entity is equipped with or uses an automatic train control system for managing train operations.
-
C.
usesRailwaySignallingSystem
Indicates that one entity operates or applies a particular railway signalling system in the context of train or rail traffic control.
-
D.
hasAutomaticFareCollection
Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
-
E.
hasAutomaticTrainAnnouncements
Indicates that a transportation system or vehicle provides automated audio or visual announcements about train operations or stops.
- 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_69e24551ec7881909a9c924dbea155f6 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f179b822988190b5368ac1f4e1d70a |
completed | April 29, 2026, 3:23 a.m. |
| PD | Predicate disambiguation | batch_69eed2b88d88819096015deb6a648801 |
completed | April 27, 2026, 3:06 a.m. |
Created at: April 17, 2026, 3:24 p.m.