Triple
T15883857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WrestleMania 31 |
E385139
|
entity |
| Predicate | MoneyInTheBankCashInType |
P120915
|
FINISHED |
| Object | in-match cash-in |
—
|
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: in-match cash-in | Statement: [WrestleMania 31, MoneyInTheBankCashInType, in-match cash-in]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MoneyInTheBankCashInType Context triple: [WrestleMania 31, MoneyInTheBankCashInType, in-match cash-in]
-
A.
hasCashForm
Indicates that something exists or is available specifically in the form of cash.
-
B.
denominationType
Indicates the specific category or kind of denomination associated with an entity, such as its type within a broader classification of denominations.
-
C.
currencyOfDenomination
Indicates that one currency unit is a specific denomination or face value within another currency system.
-
D.
typeOfBanknotes
Indicates a relationship where one entity specifies the kind or category of banknotes associated with another entity.
-
E.
hasBanknotes
Indicates that an entity possesses or contains one or more banknotes.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142c3e18c8190bb7b023f4a0eaebb |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:51 a.m.