Triple
T30142694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volkswagen emissions scandal |
E766169
|
entity |
| Predicate | mainConsequence |
P812
|
FINISHED |
| Object | vehicle recalls |
—
|
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: vehicle recalls | Statement: [Volkswagen emissions scandal, mainConsequence, vehicle recalls]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainConsequence Context triple: [Volkswagen emissions scandal, mainConsequence, vehicle recalls]
-
A.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
consequenceOfInfluence
Indicates that one event, state, or condition occurs as a result of the influence or impact exerted by another.
-
C.
significantEventConsequence
Indicates that one event leads to an important or impactful consequence for another event, state, or entity.
-
D.
consequenceInText
Indicates that one event, action, or state is presented in the text as a consequence or result of another.
-
E.
unexpectedConsequenceOf
Indicates that one event, action, or condition occurs as an unforeseen or unintended result of another.
- 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_69f2247909048190ae86c2160cf8b566 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 29, 2026, 7:18 p.m.