Triple
T16715216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nemunas River |
E406206
|
entity |
| Predicate | basinAreaInCountry |
P28955
|
FINISHED |
| Object | approximately 46,700 square kilometers in Lithuania |
—
|
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: approximately 46,700 square kilometers in Lithuania | Statement: [Nemunas River, basinAreaInCountry, approximately 46,700 square kilometers in Lithuania]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basinAreaInCountry Context triple: [Nemunas River, basinAreaInCountry, approximately 46,700 square kilometers in Lithuania]
-
A.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
-
B.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
C.
drainageAreaApprox
chosen
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
D.
lakeArea
Indicates the surface area measurement of a lake.
-
E.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e38654ee4c8190abf36c29d6610a96 |
completed | April 18, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69e319c379f88190ac0adf812486f598 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:20 a.m.