Triple
T15866515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Náměšť nad Oslavou Air Base |
E384725
|
entity |
| Predicate | hasTacticalAviationFacilities |
P120822
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Náměšť nad Oslavou Air Base, hasTacticalAviationFacilities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTacticalAviationFacilities Context triple: [Náměšť nad Oslavou Air Base, hasTacticalAviationFacilities, yes]
-
A.
hasGeneralAviationFacilities
Indicates that a location or airport provides facilities and services specifically for general aviation operations.
-
B.
operatesAirbasesIn
Indicates that an entity manages, controls, or conducts operations at airbases located within a specified area or jurisdiction.
-
C.
usesAirbase
Indicates that one entity operates from, accesses, or conducts activities at a particular airbase.
-
D.
hasFormerMilitaryAirfield
Indicates that an entity possesses or is associated with an airfield that was previously used for military purposes but is no longer active as such.
-
E.
hasEmergencyAirstrip
Indicates that an entity possesses or includes an airstrip specifically designated and equipped for emergency use.
- F. None of above. chosen
Provenance (4 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e174de2cd48190ab18e48c9f051a2a |
completed | April 16, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69e142b976c081908d3ba3e705419f3a |
completed | April 16, 2026, 8:12 p.m. |
| PDg | Predicate description generation | batch_69e174da2c2c819099ec46616798245a |
completed | April 16, 2026, 11:46 p.m. |
Created at: April 10, 2026, 4:50 a.m.