Triple
T33584464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark 39 nuclear bomb |
E860241
|
entity |
| Predicate | safetyLessonsInfluence |
P103131
|
FINISHED |
| Object | U.S. nuclear weapon safety design |
—
|
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: U.S. nuclear weapon safety design | Statement: [Mark 39 nuclear bomb, safetyLessonsInfluence, U.S. nuclear weapon safety design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyLessonsInfluence Context triple: [Mark 39 nuclear bomb, safetyLessonsInfluence, U.S. nuclear weapon safety design]
-
A.
safetyLesson
Indicates that an entity conducts, provides, or is involved in a lesson or instruction focused on safety practices or precautions.
-
B.
safetyImplication
chosen
Indicates that one entity has a consequence, effect, or relevance for the safety or risk level associated with another entity or situation.
-
C.
safetyConcept
Indicates that something embodies, represents, or is associated with a principle, idea, or framework related to safety.
-
D.
safetyRegulationEffect
Indicates how a safety regulation influences or changes the conditions, behaviors, or outcomes associated with the regulated entities.
-
E.
safetyAdvice
Indicates that one entity provides guidance or recommendations to another entity about how to avoid danger or reduce risk in a particular context.
- 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_69f3497e70e48190951c94d072879bec |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:40 a.m.