Triple
T4703979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L Reactor |
E104343
|
entity |
| Predicate | safetyEvent |
P30182
|
FINISHED |
| Object | experienced fuel assembly failures and leaks during operation |
—
|
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: experienced fuel assembly failures and leaks during operation | Statement: [L Reactor, safetyEvent, experienced fuel assembly failures and leaks during operation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyEvent Context triple: [L Reactor, safetyEvent, experienced fuel assembly failures and leaks during operation]
-
A.
safetyOutcome
Indicates the resulting condition or consequence related to safety that arises from an action, event, or situation.
-
B.
safety
Indicates that an entity provides, ensures, or is associated with protection from harm, danger, or risk for another entity or within a given context.
-
C.
emergencyEvent
Indicates that an urgent, unexpected, and potentially harmful situation or incident has occurred requiring immediate attention or response.
-
D.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
E.
safetyRelevant
chosen
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
- 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_69bd43e9b88481908582103dcadff3d9 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650ad0f88190844bfcb46b3071c2 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd621ba7448190a53ab1e2897acf71 |
completed | March 20, 2026, 3:04 p.m. |
Created at: March 20, 2026, 1:17 p.m.