Triple
T28252831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jordan River–Great Salt Lake basin |
E712357
|
entity |
| Predicate | terminalLakeSalinity |
P2853
|
FINISHED |
| Object | hypersaline |
—
|
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: hypersaline | Statement: [Jordan River–Great Salt Lake basin, terminalLakeSalinity, hypersaline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terminalLakeSalinity Context triple: [Jordan River–Great Salt Lake basin, terminalLakeSalinity, hypersaline]
-
A.
salinityTrend
Indicates how the salinity level of a given environment or water body changes over time (e.g., increasing, decreasing, or remaining stable).
-
B.
salinity
chosen
Indicates the concentration of dissolved salts present in or affecting something, typically a body of water or environment.
-
C.
maximumLake
Indicates that the subject entity is the lake with the greatest value (such as size, volume, or another specified measure) among a given set of lakes.
-
D.
mouthLake
Indicates the location where a river or stream flows into and forms part of a lake.
-
E.
salinityRegime
Indicates the pattern or level of salt concentration characterizing an environment or system over time.
- 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 11:06 p.m.