Triple
T19425573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AAR-02-01 |
E485970
|
entity |
| Predicate | includesSafetyRecommendationOn |
P97924
|
FINISHED |
| Object | horizontal stabilizer trim system inspection |
—
|
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: horizontal stabilizer trim system inspection | Statement: [AAR-02-01, includesSafetyRecommendationOn, horizontal stabilizer trim system inspection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesSafetyRecommendationOn Context triple: [AAR-02-01, includesSafetyRecommendationOn, horizontal stabilizer trim system inspection]
-
A.
safetyAdvice
chosen
Indicates that one entity provides guidance or recommendations to another entity about how to avoid danger or reduce risk in a particular context.
-
B.
safetyCategory
Indicates the classification of something according to its level or type of safety.
-
C.
safetyRationale
Indicates the reasoning or justification provided to explain how and why something is considered safe or made safe.
-
D.
safetyRelevant
Indicates that the associated entity, condition, or information has a direct impact on safety or is critical for preventing harm or accidents.
-
E.
safetyResponse
Indicates how an entity reacts or what measures it takes in response to a potential or actual safety-related 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_69d8e8d688f881909c85104a62e09d8a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e63218772c8190a48b6cb01bd12b73 |
completed | April 20, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69e4fd68b1f881908d273de1fee81a75 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:37 p.m.