Triple
T15134773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mohar (historical currency of Nepal) |
E361525
|
entity |
| Predicate | featureOnReverse |
P1603
|
FINISHED |
| Object | religious or symbolic motifs |
—
|
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: religious or symbolic motifs | Statement: [Mohar (historical currency of Nepal), featureOnReverse, religious or symbolic motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featureOnReverse Context triple: [Mohar (historical currency of Nepal), featureOnReverse, religious or symbolic motifs]
-
A.
hasReverseFeature
Indicates that one entity possesses a feature that functions in the opposite or reverse manner of another related feature.
-
B.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
C.
featuresInversion
Indicates that one entity exhibits or incorporates an inversion of another entity, such as a reversed, mirrored, or otherwise inverted form or structure.
-
D.
badgeReverseDesign
chosen
Indicates the design or imagery that appears on the reverse (back) side of a badge.
-
E.
isOnRearPlate
Indicates that one entity is positioned on or attached to the rear plate of 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b3f6f48190b1ed7c7b28feb7a6 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.