Triple
T24352064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Automobilwerk Eisenach |
E613817
|
entity |
| Predicate | hadBodyStyleRange |
P74532
|
FINISHED |
| Object | sedans |
—
|
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: sedans | Statement: [Automobilwerk Eisenach, hadBodyStyleRange, sedans]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadBodyStyleRange Context triple: [Automobilwerk Eisenach, hadBodyStyleRange, sedans]
-
A.
bodyStyleProduced
Indicates that a particular body style was manufactured or produced by a given entity (such as a company, plant, or production line).
-
B.
hasWideBodyVariant
Indicates that an entity has a corresponding wide-body version or variant of itself.
-
C.
bodyStyleCategory
chosen
Indicates the general body style classification or category that an item (such as a vehicle or product) belongs to.
-
D.
hasBodyColor
Indicates that an entity possesses a particular body color as one of its attributes.
-
E.
appliesToBodyType
Indicates that something (such as a rule, feature, or specification) is relevant or applicable to a particular body type.
- 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_69e2d7ddd29481909e7f539a6072bd71 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f293467a508190937b9614870e243e |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:59 a.m.