Triple
T8660603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Magadi |
E205537
|
entity |
| Predicate | waterPH |
P83946
|
FINISHED |
| Object | alkaline |
—
|
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: alkaline | Statement: [Lake Magadi, waterPH, alkaline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: waterPH Context triple: [Lake Magadi, waterPH, alkaline]
-
A.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
-
B.
waterVolume
Indicates the amount of water present in or associated with an entity, typically measured as a volume.
-
C.
waterType
Indicates the specific kind or category of water associated with an entity (e.g., fresh, salt, brackish).
-
D.
waterPresence
Indicates the existence or amount of water present in or around a specified entity or location.
-
E.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
- 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_69ca8350897c819086cde7596fbe5fe7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc48701c748190a5f7bd9e2da0e5e9 |
completed | March 31, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69cc4564e018819081036722f3e42a71 |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc46c330bc8190a9b644078881c6ff |
completed | March 31, 2026, 10:12 p.m. |
Created at: March 30, 2026, 6:30 p.m.