Triple
T23689716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Follis |
E585262
|
entity |
| Predicate | typicalReverseDesign |
P103246
|
FINISHED |
| Object | large denomination mark M |
—
|
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: large denomination mark M | Statement: [Follis, typicalReverseDesign, large denomination mark M]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalReverseDesign Context triple: [Follis, typicalReverseDesign, large denomination mark M]
-
A.
typicalReverseType
chosen
Indicates that the subject is the usual or canonical inverse relation type of the given predicate.
-
B.
previousReverseDesign
Indicates that one entity is the immediately preceding version or design in a reverse-ordered design sequence relative to another entity.
-
C.
reverseDesigns
Indicates that one entity creates or specifies designs that are the reverse or inverse configuration of another entity’s designs.
-
D.
reverseDesignTitle
Indicates that one design’s title is the reverse or inverse counterpart of another design’s title.
-
E.
reverseDesignSubject
Indicates that the subject is the entity for which a design or plan is derived by reversing or backtracking from an existing outcome or artifact.
- 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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5c0a218819096c2d174b004c47d |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.