Triple
T26341011
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Traditional Craft of Japan |
E662645
|
entity |
| Predicate | exampleCraft |
P163723
|
FINISHED |
| Object | Satsuma ware |
—
|
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: Satsuma ware | Statement: [Traditional Craft of Japan, exampleCraft, Satsuma ware]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exampleCraft Context triple: [Traditional Craft of Japan, exampleCraft, Satsuma ware]
-
A.
exampleCraft
chosen
Indicates that an entity creates, designs, or skillfully produces another entity, typically as a crafted example or artifact.
-
B.
hasCraft
Indicates a relationship where an entity possesses, operates, or is associated with a particular vehicle, vessel, or other craft.
-
C.
isCraftProduct
Indicates that something is a product created through skilled manual craftsmanship, often in small-scale or artisanal production rather than mass manufacturing.
-
D.
crea
Indicates that one entity creates, produces, or brings into existence another entity.
-
E.
craftEconomy
Indicates an economic relationship where goods or value are produced, exchanged, or sustained through crafting activities or artisanal production.
- 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_69ee81304194819092e20e0fae3aee07 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 26, 2026, 10:39 p.m.