Triple
T30115035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spooner Act |
E765391
|
entity |
| Predicate | authorizedPurchaseAmount |
P75110
|
FINISHED |
| Object | $40,000,000 |
—
|
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: $40,000,000 | Statement: [Spooner Act, authorizedPurchaseAmount, $40,000,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: authorizedPurchaseAmount Context triple: [Spooner Act, authorizedPurchaseAmount, $40,000,000]
-
A.
fundingAuthorizationAmount
chosen
Indicates the specific amount of money that has been formally approved or authorized to fund something.
-
B.
authorizedBondAmount
Indicates the maximum bond value that has been formally approved or permitted for issuance or use in a given context.
-
C.
valueInCents
Indicates that one entity specifies the monetary value of another entity expressed in cents.
-
D.
paymentAmount
Indicates the specific monetary value involved in a payment transaction between parties.
-
E.
offeredAmount
Indicates the specific quantity or value that one party proposes to give or pay to another in the context of an offer.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: April 29, 2026, 7:11 p.m.