Triple
T4787703
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | modified Volkswagen Touareg |
E106522
|
entity |
| Predicate | modificationOrigin |
P58428
|
FINISHED |
| Object | aftermarket tuning company |
—
|
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: aftermarket tuning company | Statement: [modified Volkswagen Touareg, modificationOrigin, aftermarket tuning company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modificationOrigin Context triple: [modified Volkswagen Touareg, modificationOrigin, aftermarket tuning company]
-
A.
modification
Indicates a change made to an existing entity, altering its properties, structure, or state from a prior version.
-
B.
alternativeOrigin
Indicates that an entity has a different or secondary source, starting point, or provenance compared to its primary or usual origin.
-
C.
laterModification
Indicates that one entity is a modification or revision that occurs after another in time.
-
D.
mayBeModifiedBy
Indicates that an entity has the potential to be altered, changed, or updated by another entity or process.
-
E.
classOrigin
Indicates the original class or category from which an entity is derived, instantiated, or classified.
- F. None of above. chosen
Provenance (4 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_69bd43f4a9588190bf73e20bc27c03cc |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65da229c81909c703393f7b9b71d |
completed | March 20, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69bd622e1b408190806c15c61519fc74 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:22 p.m.