Triple
T24160322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Rukwa |
E598813
|
entity |
| Predicate | hasWaterLevelCharacteristic |
P154821
|
FINISHED |
| Object | highly variable water level |
—
|
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: highly variable water level | Statement: [Lake Rukwa, hasWaterLevelCharacteristic, highly variable water level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterLevelCharacteristic Context triple: [Lake Rukwa, hasWaterLevelCharacteristic, highly variable water level]
-
A.
hasNormalWaterLevel
Indicates that an entity’s water level is within the expected or standard range, neither abnormally high nor low.
-
B.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
C.
hasWaterDepthCategory
Indicates the classification of something based on the range or category of its water depth.
-
D.
hasBottomWater
Indicates that an entity contains or is associated with water specifically located at its bottom or lowest part.
-
E.
controlsWaterLevelOf
Indicates that one entity has the ability or authority to regulate or adjust the water level of another entity or system.
- F. None of above. chosen
Provenance (4 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_69e288cb0a3081909ef221744f274384 |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e0e8b8c481908390c2dcff4e856b |
completed | April 29, 2026, 10:43 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
| PDg | Predicate description generation | batch_69f1785afe3c81909be28986ffe944bf |
completed | April 29, 2026, 3:17 a.m. |
Created at: April 17, 2026, 11:32 p.m.