Triple
T38235634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America’s Beautiful National Parks Quarter Dollar Coin Act of 2008 |
E1013612
|
entity |
| Predicate | maximumNumberOfDesigns |
P107904
|
FINISHED |
| Object | 56 |
—
|
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: 56 | Statement: [America’s Beautiful National Parks Quarter Dollar Coin Act of 2008, maximumNumberOfDesigns, 56]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumNumberOfDesigns Context triple: [America’s Beautiful National Parks Quarter Dollar Coin Act of 2008, maximumNumberOfDesigns, 56]
-
A.
numberOfDesigns
chosen
Indicates the quantitative count of designs associated with a given entity or context.
-
B.
maxDesignReuses
Indicates the maximum number of times a given design can be reused within a specified context or system.
-
C.
maxNumberOfValues
Indicates the maximum count of distinct values that may be associated with a given entity or property in this relationship.
-
D.
numberOfDesignations
Indicates the count of distinct designations or titles associated with a given entity.
-
E.
maximumNumberOfUsers
Indicates the highest allowable or supported number of users associated with or participating in a given context or system.
- 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_69f76dd72a248190a5fe18db2bd1eb15 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fda94697c4819081291967202248be |
completed | May 8, 2026, 9:13 a.m. |
| PD | Predicate disambiguation | batch_69fda5973fcc8190a57daef31fb70a49 |
completed | May 8, 2026, 8:57 a.m. |
Created at: May 3, 2026, 4:30 p.m.