Triple
T10449986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José María Córdova International Airport |
E246393
|
entity |
| Predicate | publicOrMilitary |
P93797
|
FINISHED |
| Object | public |
—
|
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: public | Statement: [José María Córdova International Airport, publicOrMilitary, public]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: publicOrMilitary Context triple: [José María Córdova International Airport, publicOrMilitary, public]
-
A.
civilOrMilitary
chosen
Indicates that something is classified as either civil (non-military) or military in nature or function.
-
B.
isCivilMilitary
Indicates that an entity or relationship involves both civilian and military components or functions.
-
C.
civilianEligibility
Indicates that an entity meets the criteria or conditions required to be classified or treated as a civilian in a given context.
-
D.
isMilitaryOnly
Indicates that something is restricted exclusively to military use or participation, excluding civilians or non-military entities.
-
E.
hasMilitaryStatus
Indicates that an entity possesses a specific military affiliation, role, or status (such as active duty, reserve, or veteran).
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe09af04819083db42f4de4cb0a9 |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:17 p.m.