Triple
T23072578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophie Prize |
E575235
|
entity |
| Predicate | typicalAmount |
P22091
|
FINISHED |
| Object | 100000 USD |
—
|
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: 100000 USD | Statement: [Sophie Prize, typicalAmount, 100000 USD]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAmount Context triple: [Sophie Prize, typicalAmount, 100000 USD]
-
A.
typicalRate
Indicates the standard or commonly expected rate at which something occurs, is charged, or is applied in a given context.
-
B.
typicalAwardAmount
chosen
Indicates the usual or most common amount of an award given in this relationship.
-
C.
previousStandardAmount
Indicates the amount or value that was in effect under the immediately preceding standard or baseline before the current one.
-
D.
typicalInvestmentSize
Indicates the usual or most common amount of money invested in a single investment or deal.
-
E.
typicalBottleCount
Indicates the usual or standard number of bottles associated with something under normal conditions.
- 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_69e245be28d48190ad1348d5a73db37d |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18c60fa6c81908496f181c7d62033 |
completed | April 29, 2026, 4:43 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:56 p.m.