Triple
T14295318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siemens Avanto |
E354422
|
entity |
| Predicate | hasBodyConstruction |
P19785
|
FINISHED |
| Object | articulated steel or aluminium car bodies |
—
|
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: articulated steel or aluminium car bodies | Statement: [Siemens Avanto, hasBodyConstruction, articulated steel or aluminium car bodies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyConstruction Context triple: [Siemens Avanto, hasBodyConstruction, articulated steel or aluminium car bodies]
-
A.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
B.
hasBodyPlanFeature
Indicates that an organism’s body plan includes a specific structural or morphological feature.
-
C.
hasTopBody
Indicates that one entity possesses or is characterized by a primary upper body section.
-
D.
carbodyMaterial
chosen
Indicates the material from which a vehicle’s body or main structural shell is made.
-
E.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717b35ec81908968994e65737c66 |
completed | April 14, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69de2a8f81f08190af737e1654847aa6 |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:11 a.m.