Triple
T2144361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rentenmark |
E47029
|
entity |
| Predicate | faceValueRange |
P13474
|
FINISHED |
| Object | 1 to 1000 Rentenmark banknotes |
—
|
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: 1 to 1000 Rentenmark banknotes | Statement: [Rentenmark, faceValueRange, 1 to 1000 Rentenmark banknotes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceValueRange Context triple: [Rentenmark, faceValueRange, 1 to 1000 Rentenmark banknotes]
-
A.
faceValueUnit
Indicates the unit of measurement in which the face value of something (such as a financial instrument or item) is expressed.
-
B.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
C.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
D.
typicalRange
chosen
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
E.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
- 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_69a88a1933e0819094f18426ed74180f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbeaa14bc81908486683decd7ae42 |
completed | March 7, 2026, 5:59 a.m. |
| PD | Predicate disambiguation | batch_69abbd9846e88190b6c2941dd9ce7749 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:44 p.m.