Triple
T31016298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fukushima Daini Nuclear Power Plant |
E790334
|
entity |
| Predicate | reactorScramAfterEarthquake |
P170915
|
FINISHED |
| Object | all 4 units |
—
|
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: all 4 units | Statement: [Fukushima Daini Nuclear Power Plant, reactorScramAfterEarthquake, all 4 units]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reactorScramAfterEarthquake Context triple: [Fukushima Daini Nuclear Power Plant, reactorScramAfterEarthquake, all 4 units]
-
A.
reactor4StatusDuringAccident
Indicates the operational or physical condition of reactor 4 specifically during the time of the accident.
-
B.
reactor2StatusDuringAccident
Indicates the operational or physical condition of reactor 2 throughout the duration of an accident event.
-
C.
reactor3StatusDuringAccident
Indicates the operational or physical condition of reactor 3 specifically during the time period of an accident.
-
D.
reactorInvolvedInAccident
Indicates that a specific reactor participated in, contributed to, or was directly affected by a particular accident event.
-
E.
reactor1StatusDuringAccident
Indicates the operational or physical condition of reactor 1 throughout the duration of an accident event.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:57 p.m.