Triple
T36188513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Towuti |
E1046916
|
entity |
| Predicate | hasWaterChemistry |
P63489
|
FINISHED |
| Object | low nutrient levels |
—
|
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: low nutrient levels | Statement: [Lake Towuti, hasWaterChemistry, low nutrient levels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterChemistry Context triple: [Lake Towuti, hasWaterChemistry, low nutrient levels]
-
A.
hasWaterCharacteristics
chosen
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
B.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
C.
waterPH
Indicates the acidity or alkalinity level (pH value) of a given body or sample of water.
-
D.
hasWaterClarity
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
-
E.
usesWaterTreatment
Indicates that an entity applies or relies on a water treatment process or system in its operations or activities.
- 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_69f76e3d4fbc81908c159c7beeb4ce00 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:08 p.m.