Triple
T140572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | atomic bombing of Nagasaki |
E2840
|
entity |
| Predicate | hasLongTermEffects |
P812
|
FINISHED |
| Object | radiation sickness |
—
|
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: radiation sickness | Statement: [atomic bombing of Nagasaki, hasLongTermEffects, radiation sickness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLongTermEffects Context triple: [atomic bombing of Nagasaki, hasLongTermEffects, radiation sickness]
-
A.
hasConsequence
chosen
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
C.
lifespan
Indicates the duration of time between an entity’s birth (or creation) and its death (or end).
-
D.
hasLongTermDatasetSince
Indicates that an entity has maintained or used a particular dataset continuously starting from a specified point in time.
-
E.
hasMean
Indicates that one entity possesses, exhibits, or is characterized by a particular mean value or average.
- 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_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. |
Created at: Feb. 28, 2026, 2:31 a.m.