Triple
T18248326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA 2200-series railcars |
E437012
|
entity |
| Predicate | carbodyFeature |
P19785
|
FINISHED |
| Object | fluted stainless-steel sides |
—
|
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: fluted stainless-steel sides | Statement: [CTA 2200-series railcars, carbodyFeature, fluted stainless-steel sides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: carbodyFeature Context triple: [CTA 2200-series railcars, carbodyFeature, fluted stainless-steel sides]
-
A.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
B.
carBodyProfile
Indicates the overall shape, contours, and structural outline that define a car’s external body form.
-
C.
chassisFeature
Indicates that a particular feature, component, or characteristic is part of or associated with a chassis.
-
D.
featuresVehicle
Indicates that one entity includes, presents, or prominently incorporates a particular vehicle as part of its content, composition, or offering.
-
E.
carBodyStyle
Indicates the specific body configuration or design style that characterizes a car (e.g., sedan, hatchback, SUV).
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4f7e89b288190a286797ec2cd60a8 |
completed | April 19, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69e44fcdee748190bae6fb76e0cb22f3 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:33 a.m.