Triple
T53777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | atomic bombing of Hiroshima |
E1059
|
entity |
| Predicate | injuriesEstimate |
P661
|
FINISHED |
| Object | 70000 or more injured |
—
|
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: 70000 or more injured | Statement: [atomic bombing of Hiroshima, injuriesEstimate, 70000 or more injured]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: injuriesEstimate Context triple: [atomic bombing of Hiroshima, injuriesEstimate, 70000 or more injured]
-
A.
casualtiesEstimate
chosen
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
B.
economicDamage
Indicates that one entity causes or experiences financial loss, harm, or negative economic impact as a result of another entity or event.
-
C.
estimatedCostComment
Indicates a textual note or explanation associated with an estimated cost, such as rationale, assumptions, or additional details about that estimate.
-
D.
damagedIn
Indicates that an entity has suffered harm, impairment, or destruction as a result of a specified event, process, or condition.
-
E.
damageYear
Indicates the year in which the damage to an entity occurred or was recorded.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b3a9e848190b80de3c858678b3a |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ac52fb08190aa7c38f83434f795 |
completed | Feb. 28, 2026, 1:54 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.