Triple
T1980418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kansai Airports |
E43011
|
entity |
| Predicate | typeOfBusinessEntity |
P3580
|
FINISHED |
| Object | consortium |
—
|
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: consortium | Statement: [Kansai Airports, typeOfBusinessEntity, consortium]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfBusinessEntity Context triple: [Kansai Airports, typeOfBusinessEntity, consortium]
-
A.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
B.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
-
C.
organizationType
chosen
Indicates the specific category or classification of an organization in terms of its nature, structure, or primary function.
-
D.
employerType
Indicates the classification or category of an employer in relation to the entity (e.g., public, private, nonprofit, self-employed).
-
E.
organizationTypeOfHolder
Indicates that a specified organization serves as the type or category of the holder in the given relationship.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.