Triple
T3176370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Capital International Airport Company Limited |
E66473
|
entity |
| Predicate | hasMajorRevenueSource |
P7220
|
FINISHED |
| Object | aeronautical fees |
—
|
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: aeronautical fees | Statement: [Beijing Capital International Airport Company Limited, hasMajorRevenueSource, aeronautical fees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorRevenueSource Context triple: [Beijing Capital International Airport Company Limited, hasMajorRevenueSource, aeronautical fees]
-
A.
majorRevenueSource
chosen
Indicates that one entity serves as the primary or dominant source of revenue for another entity.
-
B.
isMajorSourceOf
Indicates that one entity serves as a primary or dominant origin, cause, or provider of another entity or effect.
-
C.
hasWealthSource
Indicates that an entity derives its wealth or financial resources from a specified source.
-
D.
revenueSources
Indicates the relationship identifying where an entity’s revenue comes from or the different streams that generate its income.
-
E.
hasMajorEmployer
Indicates that an entity has a primary or most significant employer with which it is chiefly affiliated for work or occupation.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69b0bec8190957913b44d876079 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.