Triple
T20803117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ENE |
E512088
|
entity |
| Predicate | associatedCompanyScandalType |
P29490
|
FINISHED |
| Object | accounting fraud |
—
|
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: accounting fraud | Statement: [ENE, associatedCompanyScandalType, accounting fraud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCompanyScandalType Context triple: [ENE, associatedCompanyScandalType, accounting fraud]
-
A.
associatedScandal
chosen
Indicates a relationship where an entity is linked to, involved in, or notably connected with a particular scandal.
-
B.
notoriouslyAssociatedWith
Indicates a widely recognized and often negative or infamous association between one entity and another.
-
C.
disgracedFor
Indicates that an entity has lost honor, respect, or status specifically because of the associated reason, action, or circumstance.
-
D.
associatedWithAccusation
Indicates a relationship where an entity is linked or connected to a specific accusation or charge.
-
E.
hasUnderlyingCompanyWellKnownFor
Indicates that an entity is associated with an underlying company that is widely recognized or notable.
- 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2b2d5688190aaa58a2594d4787c |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:39 p.m.