Triple
T9953959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Springfield Nuclear Power Plant façade |
E195397
|
entity |
| Predicate | hasFictionalHazard |
P60749
|
FINISHED |
| Object | radioactive leakage |
—
|
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: radioactive leakage | Statement: [Springfield Nuclear Power Plant façade, hasFictionalHazard, radioactive leakage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalHazard Context triple: [Springfield Nuclear Power Plant façade, hasFictionalHazard, radioactive leakage]
-
A.
hasFictionalEventType
Indicates that something is associated with, characterized by, or classified under a particular type or category of fictional event.
-
B.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
-
C.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
D.
hasRiskInFiction
chosen
Indicates that a subject is associated with a potential danger, threat, or harmful outcome within a fictional or narrative context.
-
E.
hasFictionalIssue
Indicates that one entity possesses, is associated with, or is characterized by a particular fictional problem, flaw, or complication.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:46 p.m.