Triple
T3967500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alliance of American Football |
E92250
|
entity |
| Predicate | TomDundonInvestmentAmount |
P482
|
FINISHED |
| Object | $250 million committed (reported) |
—
|
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: $250 million committed (reported) | Statement: [Alliance of American Football, TomDundonInvestmentAmount, $250 million committed (reported)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TomDundonInvestmentAmount Context triple: [Alliance of American Football, TomDundonInvestmentAmount, $250 million committed (reported)]
-
A.
typicalInvestmentSize
Indicates the usual or most common amount of money invested in a single investment or deal.
-
B.
owedMoneyTo
Indicates that one entity has a financial obligation or debt that must be paid to another entity.
-
C.
totalAidAmountUSD
Indicates the total monetary value of aid provided, expressed in U.S. dollars.
-
D.
valueInUSD
Indicates that a given amount or asset is expressed or evaluated in terms of its monetary value in United States dollars (USD).
-
E.
monetaryValue
chosen
Indicates the amount of money associated with an entity, event, or transaction.
- 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_69aed96624188190ac8c45bb57ab72b5 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaca33e4819091957c7915857a42 |
completed | March 9, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69aef8f252b081909749d40440d372b2 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:32 p.m.