Triple
T22960478
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Ebble |
E570880
|
entity |
| Predicate | hasTypicalWaterColor |
P13022
|
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 Ebble, hasTypicalWaterColor, clear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalWaterColor Context triple: [River Ebble, hasTypicalWaterColor, clear]
-
A.
hasWaterColor
chosen
Indicates that an entity possesses or is characterized by a particular color of water.
-
B.
hasDistinctWaterColorFor
Indicates that one entity exhibits a water color that is noticeably different or unique compared to another specified entity or context.
-
C.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
-
D.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
-
E.
hasWaterClarity
Indicates the degree to which water in a given context is clear, transparent, or free from visible impurities.
- 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f3c96081909abd6ec32103d4c3 |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:47 p.m.