Triple
T84086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F.D. Roosevelt State Park |
E1691
|
entity |
| Predicate | distinction |
P3450
|
FINISHED |
| Object | largest state park in Georgia |
—
|
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: largest state park in Georgia | Statement: [F.D. Roosevelt State Park, distinction, largest state park in Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distinction Context triple: [F.D. Roosevelt State Park, distinction, largest state park in Georgia]
-
A.
uniformDistinction
Indicates that a clear and consistent difference is maintained between two or more entities within a given context.
-
B.
separates
Indicates that one entity divides, parts, or keeps other entities apart from each other.
-
C.
isDistinctFrom
Indicates that two entities are not identical and can be clearly distinguished from one another.
-
D.
significance
Indicates that one entity holds particular importance, influence, or meaningful impact in relation to another entity or context.
-
E.
division
Indicates a relationship where one entity is separated or partitioned into parts, groups, or sections based on some criterion or operation.
- 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_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. |
| PDg | Predicate description generation | batch_69a24f4b4658819087902414959161fb |
completed | Feb. 28, 2026, 2:13 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.