Triple
T14056704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M1 (Copenhagen Metro) |
E338237
|
entity |
| Predicate | hasAutomaticTrainControl |
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: [M1 (Copenhagen Metro), hasAutomaticTrainControl, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAutomaticTrainControl Context triple: [M1 (Copenhagen Metro), hasAutomaticTrainControl, yes]
-
A.
hasAutomaticTrainControlCompatibility
Indicates that an entity is compatible with, or supports integration with, an automatic train control (ATC) system.
-
B.
hasAutomaticFareCollection
Indicates that an entity is equipped with a system that automatically collects fares or payments from users without manual processing.
-
C.
railwayControlledBy
Indicates that the operation, management, or authority over a railway is exercised by a specified controlling entity.
-
D.
usesRailwaySignallingSystem
Indicates that one entity operates or applies a particular railway signalling system in the context of train or rail traffic control.
-
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. chosen
Provenance (4 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8e6d008190af8892f34c5cefbd |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 10:20 p.m.