Triple
T140560
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | atomic bombing of Nagasaki |
E2840
|
entity |
| Predicate | hasWeaponType |
P6014
|
FINISHED |
| Object | atomic bomb |
—
|
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 bomb | Statement: [atomic bombing of Nagasaki, hasWeaponType, atomic bomb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWeaponType Context triple: [atomic bombing of Nagasaki, hasWeaponType, atomic bomb]
-
A.
usedWeapon
Indicates that an entity employed a specific weapon as the means or tool to carry out an action or event.
-
B.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
C.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
D.
usedWarfareType
Indicates the specific type or method of warfare that an entity employed in a conflict or military context.
-
E.
hasMaterialType
Indicates that something is composed of, made from, or characterized by a specific type of material.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257c7e79c8190b3e5a2983035a972 |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a2565426c08190aab68e34a6a2d60e |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a25737f9188190b9690dce98aed83a |
completed | Feb. 28, 2026, 2:47 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.