Triple
T12157210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mereenie Sandstone |
E289603
|
entity |
| Predicate | thicknessCharacteristic |
P9690
|
FINISHED |
| Object | variable thickness across Amadeus Basin |
—
|
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: variable thickness across Amadeus Basin | Statement: [Mereenie Sandstone, thicknessCharacteristic, variable thickness across Amadeus Basin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thicknessCharacteristic Context triple: [Mereenie Sandstone, thicknessCharacteristic, variable thickness across Amadeus Basin]
-
A.
thickness
chosen
Indicates the measure of how deep or wide an object or layer is from one surface or side to its opposite.
-
B.
densityCharacteristic
Indicates that one entity specifies or characterizes the density property or density-related attribute of another entity.
-
C.
trimCharacteristic
Indicates that one entity defines or specifies a trimming-related property or feature of another entity.
-
D.
dimensionCharacteristic
Indicates that one entity specifies or describes a dimensional property or measurement characteristic of another entity.
-
E.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
- 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_69d6ab4c6710819097a9d228382dde43 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.