Triple
T37906786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish real de vellón |
E945576
|
entity |
| Predicate | metalBasis |
P26314
|
FINISHED |
| Object | silver |
—
|
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: silver | Statement: [Spanish real de vellón, metalBasis, silver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: metalBasis Context triple: [Spanish real de vellón, metalBasis, silver]
-
A.
associatedMetal
chosen
Indicates a relationship where one entity is linked or connected to a particular metal, such as by composition, usage, origin, or symbolic association.
-
B.
stateMetal
Indicates that an entity is in a metallic state or exhibits properties characteristic of a metal.
-
C.
metalColor
Indicates the color attribute associated specifically with a metal or metallic material.
-
D.
metalComparedWith
Indicates a comparison being made between two metals in terms of some property, quality, or characteristic.
-
E.
mainMetalProduced
Indicates that a location, facility, or process primarily produces a particular metal as its main output.
- 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_69f76ef20bb0819088b5b6ceecb0b8fc |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69fbbd166a488190b1bf9316b0790801 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.