Triple
T5774884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WMATA 3000-series railcar |
E127414
|
entity |
| Predicate | hasBrakingSystem |
P4166
|
FINISHED |
| Object | electric and pneumatic brakes |
—
|
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: electric and pneumatic brakes | Statement: [WMATA 3000-series railcar, hasBrakingSystem, electric and pneumatic brakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrakingSystem Context triple: [WMATA 3000-series railcar, hasBrakingSystem, electric and pneumatic brakes]
-
A.
brakeType
chosen
Indicates the specific kind or system of brakes associated with an entity.
-
B.
hasPedal
Indicates that one entity possesses or is equipped with a pedal or pedals used for operation or control.
-
C.
brakeWear
Indicates that an entity is experiencing or exhibiting wear, degradation, or reduction in effectiveness of its braking components or braking function.
-
D.
hasSafetyCharacteristic
Indicates that an entity possesses a specific safety-related property, feature, or attribute.
-
E.
brakeSupplier
Indicates that one entity serves as the supplier or provider of brakes to another entity.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02acb12c081908e4beee4a957f9f9 |
completed | March 22, 2026, 5:45 p.m. |
| PD | Predicate disambiguation | batch_69c021d0c6088190ba670ddcdbf5ca3e |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.