Triple
T33224501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark 1 nuclear bomb |
E850515
|
entity |
| Predicate | cityCasualtiesEstimate |
P176225
|
FINISHED |
| Object | tens of thousands killed immediately |
—
|
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: tens of thousands killed immediately | Statement: [Mark 1 nuclear bomb, cityCasualtiesEstimate, tens of thousands killed immediately]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityCasualtiesEstimate Context triple: [Mark 1 nuclear bomb, cityCasualtiesEstimate, tens of thousands killed immediately]
-
A.
casualtiesEstimate
Indicates an estimated number of people killed, injured, or otherwise harmed as a result of an event or incident.
-
B.
deathTollEstimate
Indicates an estimated number of deaths attributed to a particular event, cause, or period.
-
C.
nativeCasualties
Indicates that native or indigenous people suffered deaths or injuries as a result of a particular event, action, or conflict.
-
D.
militaryCasualtiesEstimate
Indicates an estimated number of people killed, wounded, or missing as a result of military conflict or operations.
-
E.
primaryCasualtiesFrom
Indicates that an entity is the main source or cause of the casualties experienced by another entity.
- 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_69f3496083dc8190b229bb6932dc548b |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:30 a.m.