Triple
T25129165
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LROP |
E629477
|
entity |
| Predicate | hasSchengenStatus |
P109217
|
FINISHED |
| Object | non-Schengen external border (as of 2024) |
—
|
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: non-Schengen external border (as of 2024) | Statement: [LROP, hasSchengenStatus, non-Schengen external border (as of 2024)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSchengenStatus Context triple: [LROP, hasSchengenStatus, non-Schengen external border (as of 2024)]
-
A.
hasSchengenArea
Indicates that a place, country, or region is part of, or included within, the Schengen Area for border-free movement.
-
B.
haveSimilarStatusInSchengen
Indicates that two entities share a comparable legal or administrative status within the Schengen area.
-
C.
supportsSchengenFlights
Indicates that an entity enables or accommodates flights operating within the Schengen Area.
-
D.
isSchengenExternalBorder
chosen
Indicates that a given border segment functions as an external boundary between the Schengen Area and non-Schengen territories.
-
E.
haveVisaLiberalizationWith
Indicates that there exists a mutual agreement or policy framework under which entities allow eased or visa-free travel between them.
- 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_69e2ff3288048190bd82c3b7f7bd0e62 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 6:28 a.m.