Triple
T24474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry S. Truman |
E487
|
entity |
| Predicate | oversawEvent |
P1766
|
FINISHED |
| Object | atomic bombings of Hiroshima and Nagasaki |
—
|
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: atomic bombings of Hiroshima and Nagasaki | Statement: [Harry S. Truman, oversawEvent, atomic bombings of Hiroshima and Nagasaki]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oversawEvent Context triple: [Harry S. Truman, oversawEvent, atomic bombings of Hiroshima and Nagasaki]
-
A.
participatedInEvent
Indicates that an entity took part in or was actively involved in a specific event.
-
B.
significantEvent
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
C.
sportsEventHosted
Indicates that a particular sports event was organized, arranged, or held by a specified host entity (such as a venue, organization, or city).
-
D.
organizes
Indicates that one entity arranges, coordinates, or structures activities, items, or people into an ordered or planned form for a particular purpose.
-
E.
overlooks
Indicates that one entity has a view toward or looks out over another entity, typically from a higher or adjacent position.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a246e94ca881908f7a7d2c0b293033 |
completed | Feb. 28, 2026, 1:37 a.m. |
| PD | Predicate disambiguation | batch_69a246560af88190961ea00b35cf9388 |
completed | Feb. 28, 2026, 1:35 a.m. |
| PDg | Predicate description generation | batch_69a246e7fac481909b0c500d4500650e |
completed | Feb. 28, 2026, 1:37 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.