Triple
T15474872
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gutenberg–Richter law |
E376757
|
entity |
| Predicate | typicalBValue |
P99172
|
FINISHED |
| Object | approximately 1 |
—
|
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: approximately 1 | Statement: [Gutenberg–Richter law, typicalBValue, approximately 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalBValue Context triple: [Gutenberg–Richter law, typicalBValue, approximately 1]
-
A.
typicalValueFor
chosen
Indicates that one entity represents a standard, representative, or commonly occurring value associated with another entity.
-
B.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
-
C.
typicalMeasure
Indicates the standard or characteristic quantitative measure typically associated with something, such as its usual size, weight, duration, or other magnitude.
-
D.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
E.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f6e859481909c3d08343b7ad27c |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:34 a.m.