Triple
T36004827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperial Fault Zone |
E1041233
|
entity |
| Predicate | maximumMagnitudeApprox |
P46842
|
FINISHED |
| Object | around 7.0 |
—
|
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: around 7.0 | Statement: [Imperial Fault Zone, maximumMagnitudeApprox, around 7.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumMagnitudeApprox Context triple: [Imperial Fault Zone, maximumMagnitudeApprox, around 7.0]
-
A.
maximumMagnitude
chosen
Indicates the greatest absolute value or intensity that a quantity, measurement, or effect can reach within a given context.
-
B.
maximumNumber
Indicates that one entity specifies the highest allowable or observed quantity, value, or count associated with another entity.
-
C.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
D.
maximumDigit
Indicates that one entity is the largest-valued digit present within another entity (such as a number or digit sequence).
-
E.
exampleMagnitude
Indicates a relationship where one entity serves as a representative or typical instance that illustrates the scale, size, or intensity (magnitude) of another entity or quantity.
- 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_69f76e2a02208190aedd1f9025a8b300 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 3, 2026, 4:07 p.m.