Triple
T36869079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KNA |
E911174
|
entity |
| Predicate | airlineOperatingCountry |
P12358
|
FINISHED |
| Object | People's Republic of China |
—
|
NE NERFINISHED |
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: People's Republic of China | Statement: [KNA, airlineOperatingCountry, People's Republic of China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineOperatingCountry Context triple: [KNA, airlineOperatingCountry, People's Republic of China]
-
A.
associatedAirportOperatorCountry
Indicates the country in which the operator of the associated airport is based or registered.
-
B.
linkedAirlineCountry
chosen
Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
-
C.
airlineNationalityOfAirline
Indicates the country or nationality with which an airline is associated.
-
D.
airLegOperatedBy
Indicates that a specific segment (leg) of an air journey is operated by a particular airline or carrier.
-
E.
countryServedByOperatedAirport
Indicates that a given country is the one whose air transport needs are served by a particular airport that operates within or for it.
- 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_69f76e80f6f0819091cba8e19b269615 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 3, 2026, 4:13 p.m.