Triple
T19450011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fell centre rail system |
E486590
|
entity |
| Predicate | brakeApplication |
P135935
|
FINISHED |
| Object | directly on centre rail |
—
|
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: directly on centre rail | Statement: [Fell centre rail system, brakeApplication, directly on centre rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brakeApplication Context triple: [Fell centre rail system, brakeApplication, directly on centre rail]
-
A.
brakeFeature
Indicates that an entity possesses or is equipped with a particular braking-related feature or capability.
-
B.
hasBraking
Indicates that an entity possesses or is equipped with a braking capability or braking system.
-
C.
brakeType
Indicates the specific kind or system of brakes associated with an entity.
-
D.
brakeDemand
Indicates that an entity is requesting or applying a braking action, specifying the needed braking force or intensity.
-
E.
brakingTestsPerformed
Indicates that one entity has carried out braking tests on another entity or system.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338caeb48190aeb1d511996984e3 |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd6e806081909053f325ba01ab6b |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004c23308190a087b7941a90725f |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:38 p.m.