Triple
T24041205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Hiz |
E595379
|
entity |
| Predicate | hasTypicalWaterClarity |
P15328
|
FINISHED |
| Object | clear |
—
|
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: clear | Statement: [River Hiz, hasTypicalWaterClarity, clear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWaterClarity Context triple: [River Hiz, hasTypicalWaterClarity, clear]
-
A.
hasWaterClarity
chosen
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
-
B.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
C.
waterAppearance
Indicates how the water involved in the situation looks or visually appears (e.g., its color, clarity, or surface condition).
-
D.
hasWaterColor
Indicates that an entity possesses or is characterized by a particular color of water.
-
E.
waterCondition
Indicates the state or quality of water affecting an entity, such as its cleanliness, safety, or suitability for a particular use.
- 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_69e288c06a908190899cad4531f32c9a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d8b7248190a4e7f152d6bfc2bc |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:57 p.m.