Triple
T12821263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Value Alliance |
E306534
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Jeju Air |
E471136
|
NE 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: Jeju Air | Statement: [Value Alliance, hasMember, Jeju Air]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeju Air Context triple: [Value Alliance, hasMember, Jeju Air]
-
A.
Jeju Air
chosen
Jeju Air is a South Korean low-cost airline that operates extensive domestic and international routes, particularly serving leisure and regional markets in East Asia.
-
B.
Asiana Airlines
Asiana Airlines is a major South Korean international airline based in Seoul, operating an extensive network of passenger and cargo services across Asia, Europe, North America, and Oceania.
-
C.
Korean Air
Korean Air is South Korea’s largest airline and flag carrier, operating extensive international and domestic passenger and cargo services worldwide.
-
D.
Jin Air
Jin Air is a South Korean low-cost airline that operates domestic and international passenger flights.
-
E.
Skymark Airlines
Skymark Airlines is a Japanese low-cost carrier based in Tokyo that operates domestic flights and some international services.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d7bdf46c448190b1faa55aaacb6317 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e9fcc8c8190a926ab0481d28f14 |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ed165188190a4cac781c753fb23 |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:31 p.m.