Triple
T20030160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MARTA heavy rail cars |
E495099
|
entity |
| Predicate | hasCarConfiguration |
P138434
|
FINISHED |
| Object | married pairs |
—
|
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: married pairs | Statement: [MARTA heavy rail cars, hasCarConfiguration, married pairs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCarConfiguration Context triple: [MARTA heavy rail cars, hasCarConfiguration, married pairs]
-
A.
hasVehicleFeature
Indicates that a vehicle possesses, includes, or is equipped with a specific feature or characteristic.
-
B.
hasAxleConfiguration
Indicates that an entity is associated with a specific arrangement or configuration of its axles.
-
C.
hasCarClass
Indicates that one entity is associated with, or categorized under, a particular class or type of car.
-
D.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
-
E.
carTypeVariant
Indicates that one car type is a specific variant or version of another car type.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66291a00c8190b0b895909f32d623 |
completed | April 20, 2026, 5:29 p.m. |
| PD | Predicate disambiguation | batch_69e54ce752748190a0a1ffddd0372271 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:36 p.m.