Triple
T25019597
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hokitika Gorge |
E626534
|
entity |
| Predicate | hasWaterColorCause |
P158706
|
FINISHED |
| Object | glacial flour suspended in water |
—
|
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: glacial flour suspended in water | Statement: [Hokitika Gorge, hasWaterColorCause, glacial flour suspended in water]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWaterColorCause Context triple: [Hokitika Gorge, hasWaterColorCause, glacial flour suspended in water]
-
A.
hasWaterColor
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.
hasWaterFeatures
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
| PDg | Predicate description generation | batch_69f47b7f657c81908174590c811a3cbf |
completed | May 1, 2026, 10:07 a.m. |
Created at: April 18, 2026, 6:06 a.m.