Triple
T4449201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Buffalo gold bullion coin |
E96365
|
entity |
| Predicate | reverseDesignSubject |
P56579
|
FINISHED |
| Object | buffalo |
—
|
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: buffalo | Statement: [American Buffalo gold bullion coin, reverseDesignSubject, buffalo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reverseDesignSubject Context triple: [American Buffalo gold bullion coin, reverseDesignSubject, buffalo]
-
A.
reverseDesigner
Indicates that one entity is the designer or creator of another entity, with the direction of the relationship reversed from a primary “designer” predicate.
-
B.
reversed
Indicates that the direction or order of a previously defined relationship or sequence between entities is inverted.
-
C.
reverseFeature
Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
-
D.
reverseMotif
Indicates that one motif is the reversed or inverted form of another motif in structure, order, or direction.
-
E.
alternateDesignation
Indicates that one entity serves as an alternative name, label, or identifier for another entity.
- F. None of above. chosen
Provenance (4 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_69b345415ba481908df738e7174448ba |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b355d5975c8190bfe8a2d5d2dbf075 |
completed | March 13, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69b34f62c180819097ced38da2052207 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b35034cd248190bae09e9d090e13ec |
completed | March 12, 2026, 11:45 p.m. |
Created at: March 12, 2026, 11:32 p.m.