Triple
T2494500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kinkisharyo light rail vehicles |
E52123
|
entity |
| Predicate | typicalCarBodyMaterial |
P19785
|
FINISHED |
| Object | stainless steel |
—
|
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: stainless steel | Statement: [Kinkisharyo light rail vehicles, typicalCarBodyMaterial, stainless steel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCarBodyMaterial Context triple: [Kinkisharyo light rail vehicles, typicalCarBodyMaterial, stainless steel]
-
A.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
B.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
C.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
D.
vehicleStandard
Indicates that something complies with, or is defined according to, a specified vehicle-related standard or regulatory specification.
-
E.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
- 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_69ab4955111c8190835bf619adec21ff |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd193fe7881909b08768c44b15049 |
completed | March 7, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69abd0b980b481908d4932bcea4a6167 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.