Triple
T7716047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lotusmiles |
E174884
|
entity |
| Predicate | earnsOn |
P30192
|
FINISHED |
| Object | Vietnam 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: Vietnam Airlines flights | Statement: [Lotusmiles, earnsOn, Vietnam Airlines flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earnsOn Context triple: [Lotusmiles, earnsOn, Vietnam Airlines flights]
-
A.
earnOn
chosen
Indicates that one entity gains income, profit, or returns as a result of another entity or activity.
-
B.
ownsWork
Indicates that one entity has legal ownership or proprietary rights over a particular work or creation.
-
C.
canEarnOn
Indicates that an entity is able or permitted to receive or generate earnings from another entity, source, or activity.
-
D.
careerEarningsApprox
Indicates an approximate total amount of money an entity has earned over the course of its career.
-
E.
incomeType
Indicates the category or source classification of an entity’s income 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_69c6995c463c8190a14458036249d419 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
Created at: March 27, 2026, 4:04 p.m.