Triple
T12620111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type 3 Indian Princess gold dollar |
E301355
|
entity |
| Predicate | reverseMotifType |
P14351
|
FINISHED |
| Object | agricultural wreath |
—
|
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: agricultural wreath | Statement: [Type 3 Indian Princess gold dollar, reverseMotifType, agricultural wreath]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseMotifType Context triple: [Type 3 Indian Princess gold dollar, reverseMotifType, agricultural wreath]
-
A.
reverseMotif
chosen
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
-
B.
reverseMotto
Indicates that one entity is the reverse (character-by-character or order-wise inverted) form of another entity’s motto or slogan.
-
C.
typicalReverseType
Indicates that the subject is the usual or canonical inverse relation type of the given predicate.
-
D.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
-
E.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617b07ec8190b714f04ae6654060 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b195108190ac25bd95e644ace4 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:13 p.m.