Triple
T9538942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pyasina River |
E230095
|
entity |
| Predicate | basinSizeInSquareKilometres |
P1641
|
FINISHED |
| Object | 182000 |
—
|
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: 182000 | Statement: [Pyasina River, basinSizeInSquareKilometres, 182000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basinSizeInSquareKilometres Context triple: [Pyasina River, basinSizeInSquareKilometres, 182000]
-
A.
drainageBasinArea
chosen
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
B.
drainageAreaApprox
Indicates that one entity has an approximate drainage area measured or characterized by the other entity.
-
C.
basinCountry
Indicates the country or countries within whose territory a river basin or drainage area is primarily located or through which it significantly extends.
-
D.
basinPartOf
Indicates that one basin is a component or subdivision of a larger basin or basin system.
-
E.
lakeArea
Indicates the surface area measurement of a lake.
- 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_69ca847b1b3081908f72bc932c17cc41 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e4df6c8190a4d1160c42daa45f |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.