Triple
T6368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warm Springs, Georgia |
E127
|
entity |
| Predicate | hasHistoricEvent |
P259
|
FINISHED |
| Object | death of Franklin D. Roosevelt in 1945 |
—
|
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: death of Franklin D. Roosevelt in 1945 | Statement: [Warm Springs, Georgia, hasHistoricEvent, death of Franklin D. Roosevelt in 1945]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricEvent Context triple: [Warm Springs, Georgia, hasHistoricEvent, death of Franklin D. Roosevelt in 1945]
-
A.
significantEvent
chosen
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
B.
hasHistoricDistrict
Indicates that an entity possesses or contains a designated historic district within its boundaries or domain.
-
C.
hasMemorial
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
D.
participatedInEvent
Indicates that an entity took part in or was actively involved in a specific event.
-
E.
hasLegacy
Indicates that an entity leaves behind a lasting impact, influence, or inheritance that continues to exist or be recognized over time.
- 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_69a23bb612708190b09f25385e4b63d1 |
completed | Feb. 28, 2026, 12:49 a.m. |
| NER | Named-entity recognition | batch_69a2421836f08190b54fc40edeb1a96b |
completed | Feb. 28, 2026, 1:17 a.m. |
| PD | Predicate disambiguation | batch_69a23fe064c881909496fd0e6b0e18d7 |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 12:54 a.m.