Triple
T9447632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midwest Airlines |
E227803
|
entity |
| Predicate | serviceReputation |
P36019
|
FINISHED |
| Object | high customer satisfaction among frequent flyers |
—
|
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: high customer satisfaction among frequent flyers | Statement: [Midwest Airlines, serviceReputation, high customer satisfaction among frequent flyers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceReputation Context triple: [Midwest Airlines, serviceReputation, high customer satisfaction among frequent flyers]
-
A.
performanceReputation
chosen
Indicates the perceived quality or reliability of an entity’s past or expected performance as judged by others.
-
B.
scoringReputation
Indicates that one entity evaluates and assigns a reputation-related score to another entity based on its behavior or performance.
-
C.
securityReputation
Indicates the assessed trustworthiness or risk level associated with an entity’s security posture or behavior.
-
D.
commercialReputation
Indicates the perceived standing or esteem of an entity in a commercial or business context, based on others’ experiences, opinions, or evaluations.
-
E.
institutionalReputationContext
Indicates the situational or environmental factors that shape or influence an institution’s reputation.
- 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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f62dfa48190bf318777d97f0f2a |
completed | April 1, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.