Triple
T14613555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OnePass |
E343019
|
entity |
| Predicate | couldEarnOn |
P67161
|
FINISHED |
| Object | Continental Airlines flights |
—
|
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: Continental Airlines flights | Statement: [OnePass, couldEarnOn, Continental Airlines flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: couldEarnOn Context triple: [OnePass, couldEarnOn, Continental Airlines flights]
-
A.
canEarnOn
chosen
Indicates that an entity is able or permitted to receive or generate earnings from another entity, source, or activity.
-
B.
canBeEarnedBy
Indicates that something (such as a reward, status, or resource) is obtainable through the actions, efforts, or qualifications of a particular entity.
-
C.
earnOn
Indicates that one entity gains income, profit, or returns as a result of another entity or activity.
-
D.
careerEarningsApprox
Indicates an approximate total amount of money an entity has earned over the course of its career.
-
E.
profitsFrom
Indicates that one entity gains financial or material benefit as a result of another entity’s actions, existence, or 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb45264988190a1df13e8b54a85bd |
completed | April 14, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69de656f9f4c81909f815b6629a9ee39 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:25 a.m.