Triple
T2199470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Joaquín de Olmedo International Airport |
E50454
|
entity |
| Predicate | openedInCurrentTerminal |
P617
|
FINISHED |
| Object | 2006 |
—
|
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: 2006 | Statement: [José Joaquín de Olmedo International Airport, openedInCurrentTerminal, 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedInCurrentTerminal Context triple: [José Joaquín de Olmedo International Airport, openedInCurrentTerminal, 2006]
-
A.
openedIn
chosen
Indicates that an entity (such as a business, event, or institution) began operating or was inaugurated in a specific time period or location.
-
B.
openedWith
Indicates that an entity is opened, initiated, or accessed using a specified tool, method, or instrument.
-
C.
openedAs
Indicates that one entity began operating, functioning, or being available to the public under the form, name, or role of another entity.
-
D.
opensInto
Indicates that one space, structure, or passage directly leads or provides access into another space or area.
-
E.
openedInConnectionWith
Indicates that one entity was opened as a direct result of, or in association with, another specific event, action, or entity.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf9e99f08190892d34485c8f2f25 |
completed | March 7, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.