Triple
T25983446
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British Airways |
E646130
|
entity |
| Predicate | safetyManagementSystem |
P128851
|
FINISHED |
| Object | ICAO-compliant SMS |
—
|
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: ICAO-compliant SMS | Statement: [British Airways, safetyManagementSystem, ICAO-compliant SMS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyManagementSystem Context triple: [British Airways, safetyManagementSystem, ICAO-compliant SMS]
-
A.
safetyPrograms
Indicates that there are organized measures, policies, or initiatives implemented to protect people or assets from harm or risk.
-
B.
safetyDepartment
Indicates that an entity is associated with, belongs to, or is managed by a safety department responsible for safety-related functions or oversight.
-
C.
hasHazardManagement
chosen
Indicates that an entity has measures, systems, or responsibilities in place to control, mitigate, or respond to identified hazards.
-
D.
safetyContext
Indicates the circumstances, conditions, or environment that affect how safe an action, object, or situation is.
-
E.
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.
- 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_69e77e881fc08190ba1c8dc7e2a07f97 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f60511cfe88190b2b88b40fb4ec269 |
completed | May 2, 2026, 2:07 p.m. |
| PD | Predicate disambiguation | batch_69f4a10480748190a2e67bd399fc435d |
completed | May 1, 2026, 12:48 p.m. |
Created at: April 22, 2026, 8:54 a.m.