Triple
T30242054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen California |
E768942
|
entity |
| Predicate | hasFreshWaterTank |
P75490
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Volkswagen California, hasFreshWaterTank, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFreshWaterTank Context triple: [Volkswagen California, hasFreshWaterTank, yes]
-
A.
hasTank
chosen
Indicates that an entity possesses, is equipped with, or contains a tank (such as a storage tank, fuel tank, or similar vessel).
-
B.
hasFreshwaterSection
Indicates that an entity includes or contains a distinct section or area composed of freshwater.
-
C.
hasCentralTank
Indicates that an entity possesses or is equipped with a primary central tank as a key component or feature.
-
D.
waterContains
Indicates that a body or volume of water holds, includes, or has within it a specified substance, object, or entity.
-
E.
hasWaterFunction
Indicates that an entity performs, provides, or is associated with a specific function or role related to water.
- 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_69f224820c048190b1435c4cc145acf1 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6df450014819099d118e5c2d697fa |
completed | May 3, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69f6de07836481908785cde9c511920b |
completed | May 3, 2026, 5:32 a.m. |
Created at: April 29, 2026, 7:39 p.m.