Triple
T14867242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Budapest Ferenc Liszt International Airport |
E349646
|
entity |
| Predicate | hasSchengenTraffic |
P33076
|
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: [Budapest Ferenc Liszt International Airport, hasSchengenTraffic, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchengenTraffic Context triple: [Budapest Ferenc Liszt International Airport, hasSchengenTraffic, yes]
-
A.
hasSchengenArea
Indicates that a place, country, or region is part of, or included within, the Schengen Area for border-free movement.
-
B.
isSchengenExternalBorder
Indicates that a given border segment functions as an external boundary between the Schengen Area and non-Schengen territories.
-
C.
supportsSchengenFlights
chosen
Indicates that an entity enables or accommodates flights operating within the Schengen Area.
-
D.
haveSimilarStatusInSchengen
Indicates that two entities share a comparable legal or administrative status within the Schengen area.
-
E.
hasBorderControlIssues
Indicates that there are problems, weaknesses, or irregularities in the enforcement or management of border controls between entities.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5776b848190bfe3a06ff261dc31 |
completed | April 15, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:55 a.m.