Triple
T7639473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leoš Janáček Airport Ostrava |
E172961
|
entity |
| Predicate | hasCargoHandlingServices |
P11980
|
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: [Leoš Janáček Airport Ostrava, hasCargoHandlingServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCargoHandlingServices Context triple: [Leoš Janáček Airport Ostrava, hasCargoHandlingServices, yes]
-
A.
hasCargoServices
chosen
Indicates that an entity provides or is equipped to handle cargo transportation or freight services for another entity or location.
-
B.
hasGroundHandlingServices
Indicates that an entity provides or is associated with ground handling services for another entity, typically in an aviation or transportation context.
-
C.
hasPassengerHandling
Indicates that an entity is responsible for or involved in managing the processes and services related to handling passengers.
-
D.
hasCargoTerminal
Indicates that a location or facility includes or is equipped with a cargo terminal for handling freight.
-
E.
hasCargoAirline
Indicates that one entity operates as a cargo airline for, or provides cargo air transport services to, another 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facc4b5481908697e662b0991e3f |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.