Triple
T84117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F.D. Roosevelt State Park |
E1691
|
entity |
| Predicate | namedForRoleOf |
P63
|
FINISHED |
| Object | 32nd President of the United States |
—
|
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: 32nd President of the United States | Statement: [F.D. Roosevelt State Park, namedForRoleOf, 32nd President of the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForRoleOf Context triple: [F.D. Roosevelt State Park, namedForRoleOf, 32nd President of the United States]
-
A.
namedAfter
chosen
Indicates that one entity has been given its name in honor of, or derived from, another entity.
-
B.
nameOf
Indicates that one entity is the name or designation of another entity.
-
C.
role
Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
-
D.
recognizedFor
Indicates that one entity is acknowledged, credited, or honored for a particular achievement, quality, contribution, or work associated with another entity.
-
E.
isAssociatedWith
Indicates that there exists a connection, relationship, or involvement between two entities without specifying its exact nature.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a24f4e73c081908d2da146226ef05e |
completed | Feb. 28, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69a24eb469548190b38c24e81f36c838 |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.