Triple
T5731497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WorldCom accounting scandal |
E126393
|
entity |
| Predicate | fraudType |
P7957
|
FINISHED |
| Object | earnings manipulation |
—
|
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: earnings manipulation | Statement: [WorldCom accounting scandal, fraudType, earnings manipulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fraudType Context triple: [WorldCom accounting scandal, fraudType, earnings manipulation]
-
A.
crimeType
chosen
Indicates the specific category or nature of the crime associated with an event or entity.
-
B.
trapType
Indicates the specific kind or category of trap associated with an entity or situation.
-
C.
accusationType
Indicates the specific category or nature of an accusation made by one party against another.
-
D.
committedCrime
Indicates that an entity has carried out or been responsible for a criminal act or offense.
-
E.
illegalActivityAssociatedWith
Indicates that there is a connection between an entity and an unlawful or criminal activity.
- 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_69c0083082288190b7478cead6b5430a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c6488881909bed4a4534d57f70 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:47 p.m.