Triple
T1979363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukushima Daiichi nuclear disaster |
E42988
|
entity |
| Predicate | healthImpact |
P19730
|
FINISHED |
| Object | increased radiation exposure for emergency workers |
—
|
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: increased radiation exposure for emergency workers | Statement: [Fukushima Daiichi nuclear disaster, healthImpact, increased radiation exposure for emergency workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthImpact Context triple: [Fukushima Daiichi nuclear disaster, healthImpact, increased radiation exposure for emergency workers]
-
A.
healthEffect
chosen
Indicates the impact or consequence that one entity has on the health or well-being of another.
-
B.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
-
C.
humanImpact
Indicates the effect or influence that human activities have on another entity, system, or environment.
-
D.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
E.
covid19Impact
Indicates the effect, consequences, or influence that COVID-19 has on a given entity, condition, or situation.
- 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_69a8871289048190b00b0d7744b7b2b1 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:36 p.m.