Triple
T12325531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thoma Bravo |
E293819
|
entity |
| Predicate | typicalDealType |
P101426
|
FINISHED |
| Object | leveraged buyout |
—
|
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: leveraged buyout | Statement: [Thoma Bravo, typicalDealType, leveraged buyout]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDealType Context triple: [Thoma Bravo, typicalDealType, leveraged buyout]
-
A.
typeOfDeal
chosen
Indicates the specific category or nature of a deal or agreement that applies between entities.
-
B.
typicalBureauType
Indicates that one entity is the standard or commonly occurring type or category of bureau associated with another entity.
-
C.
typicalUnitType
Indicates that one entity is the standard or commonly used unit type associated with measuring or expressing the other entity.
-
D.
collateralType
Indicates the kind or category of collateral associated with an obligation, agreement, or financial exposure.
-
E.
saleType
Indicates the specific category or method by which a sale is conducted or classified (e.g., retail, wholesale, auction).
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.