Triple
T7461222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FRNs |
E176252
|
entity |
| Predicate | minimumDenomination |
P77233
|
FINISHED |
| Object | 100 U.S. dollars |
—
|
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: 100 U.S. dollars | Statement: [FRNs, minimumDenomination, 100 U.S. dollars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumDenomination Context triple: [FRNs, minimumDenomination, 100 U.S. dollars]
-
A.
minorDenomination
Indicates that one entity is a smaller or subordinate unit of currency or value in relation to another entity.
-
B.
lowerDenomination
Indicates that one entity represents a monetary unit of smaller value than another entity within the same currency system.
-
C.
minimumNumber
Indicates that the associated value is the smallest or least quantity allowed, required, or observed within a given set or context.
-
D.
coinDenomination
Indicates the specific monetary value assigned to a coin within a currency system.
-
E.
fineMinimumUSD
Indicates the minimum monetary penalty amount, expressed in U.S. dollars, that applies in this context.
- 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_69c69f21632481908bf83f6c6da897e3 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f3d6cf8c8190a31cac121d151d78 |
completed | March 27, 2026, 9:17 p.m. |
| PD | Predicate disambiguation | batch_69c6f03bad9c8190bdd5abb86d37df47 |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f386daac81908ded91b397b44148 |
completed | March 27, 2026, 9:15 p.m. |
Created at: March 27, 2026, 3:38 p.m.