Triple
T4289912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake McKenzie |
E97362
|
entity |
| Predicate | sandComposition |
P18668
|
FINISHED |
| Object | almost pure silica |
—
|
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: almost pure silica | Statement: [Lake McKenzie, sandComposition, almost pure silica]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sandComposition Context triple: [Lake McKenzie, sandComposition, almost pure silica]
-
A.
hasSedimentsThat
chosen
Indicates that one entity contains, includes, or is associated with specific sediments described by the related entity.
-
B.
hasSandColor
Indicates that one entity possesses or exhibits the sand-like color of another entity or color value.
-
C.
typeOfSedimentation
Indicates the specific kind or process of sediment deposition or settling that characterizes how sediment accumulates in a given context.
-
D.
seedComposition
Indicates the relationship specifying what substances or components make up a seed.
-
E.
mountainComposition
Indicates the material or substance that makes up or predominates in a given mountain.
- 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_69b3454595848190a0e6bbb6a2bea040 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35061f5448190b3356b29a9129160 |
completed | March 12, 2026, 11:46 p.m. |
| PD | Predicate disambiguation | batch_69b347fc4c0c8190a7fcd814e27308a5 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.