Triple
T25362188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mulu Airport |
E635997
|
entity |
| Predicate | mainAirlines |
P35742
|
FINISHED |
| Object | Malaysia Airlines |
—
|
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: Malaysia Airlines | Statement: [Mulu Airport, mainAirlines, Malaysia Airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainAirlines Context triple: [Mulu Airport, mainAirlines, Malaysia Airlines]
-
A.
mainAirlineFocus
Indicates that an airline is the primary or central focus of attention, operations, or analysis in a given context.
-
B.
hasAirlines
chosen
Indicates that one entity (such as an airport, city, or country) is served by or associated with one or more airline operators.
-
C.
airTransportServedBy
Indicates that a particular air transport service (such as a route, flight, or airport operation) is provided or operated by a specified carrier or service provider.
-
D.
airlineHub
Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
-
E.
primaryHubAirline
Indicates that an airline serves as the main or principal hub carrier for a particular airport or location.
- 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_69e75a9b7cf481909f2dcdfb37d95ca7 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 21, 2026, 1:36 p.m.