Triple
T24709451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daegu International Airport |
E611986
|
entity |
| Predicate | hasCivilianTerminal |
P53208
|
FINISHED |
| Object | passenger terminal |
—
|
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: passenger terminal | Statement: [Daegu International Airport, hasCivilianTerminal, passenger terminal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCivilianTerminal Context triple: [Daegu International Airport, hasCivilianTerminal, passenger terminal]
-
A.
hasCivilianClass
Indicates that an entity is associated with or belongs to a particular civilian classification or category.
-
B.
isCivilian
Indicates that an entity is a non-military, non-combatant individual in the context of a given situation or system.
-
C.
hasCivilianIdentityIntroduced
Indicates that an entity’s civilian (non-superpowered or non-professional) identity has been revealed or established within the context of the narrative or dataset.
-
D.
hasTerminalFacility
chosen
Indicates that an entity possesses or includes a terminal facility used as an endpoint for transport, communication, or related operations.
-
E.
hasCivilianControl
Indicates that one party exercises authority or oversight over another in a civilian (non-military) capacity.
- 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f422aee0408190899efe7e24ef2b40 |
completed | May 1, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f420e92cc88190a803aecdae78a051 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 3:24 a.m.