Triple
T8193257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Visegrád Four |
E191364
|
entity |
| Predicate | hasAreaOfMemberStatesCombinedApprox |
P8028
|
FINISHED |
| Object | ~533,000 square kilometres |
—
|
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: ~533,000 square kilometres | Statement: [Visegrád Four, hasAreaOfMemberStatesCombinedApprox, ~533,000 square kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAreaOfMemberStatesCombinedApprox Context triple: [Visegrád Four, hasAreaOfMemberStatesCombinedApprox, ~533,000 square kilometres]
-
A.
areaOfMemberStatesApprox
chosen
Indicates the approximate total geographic area collectively covered by the member states of a given organization or grouping.
-
B.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
-
C.
areaTotalSquareMiles
Indicates the total geographic area of something measured in square miles.
-
D.
meanSurfaceArea_km2
Indicates the average surface area of an entity measured in square kilometers.
-
E.
landAreaSquareMiles
Indicates the size of a geographic area measured in square miles.
- 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_69ca82c5b6948190a583c096fb0a6c71 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5c1d7aa48190adbbce88b3bed1a3 |
completed | March 31, 2026, 5:31 a.m. |
| PD | Predicate disambiguation | batch_69cb36aac86081909b83636e352e0ced |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:42 p.m.