Triple
T946927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Salt Lake |
E20432
|
entity |
| Predicate | hasColoration |
P22465
|
FINISHED |
| Object | areas of pink or reddish water due to microorganisms |
—
|
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: areas of pink or reddish water due to microorganisms | Statement: [Great Salt Lake, hasColoration, areas of pink or reddish water due to microorganisms]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColoration Context triple: [Great Salt Lake, hasColoration, areas of pink or reddish water due to microorganisms]
-
A.
hasColorSymbol
Indicates that one entity is associated with another entity that serves as its representative or symbolic color.
-
B.
hasColorOption
Indicates that an entity offers or supports a particular color as one of its selectable options.
-
C.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
D.
hasColorPlay
Indicates a relationship where something exhibits or incorporates playful or varied use of color.
-
E.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bcad2481908b83575b2fb80d14 |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29f05f481908814bd11f235e9d0 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b385176081909e3e8c3f647c1fd4 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.