Triple
T10412850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miles & More |
E245435
|
entity |
| Predicate | mainBenefit |
P25020
|
FINISHED |
| Object | flight awards |
—
|
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: flight awards | Statement: [Miles & More, mainBenefit, flight awards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainBenefit Context triple: [Miles & More, mainBenefit, flight awards]
-
A.
primaryBenefit
chosen
Indicates that one entity serves as the main or most important advantage, gain, or positive outcome associated with another entity.
-
B.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
C.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
benefice
Indicates that one entity grants or bestows a benefit, favor, or advantage upon another.
-
E.
believedBenefit
Indicates that one entity considers or perceives another entity, action, or state as providing an advantage or positive outcome.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea0e17f081908fb16425f65e5808 |
completed | April 7, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:10 p.m.