Triple
T27054257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaga yuzen dyeing |
E684855
|
entity |
| Predicate | differenceFromKyoYuzen |
P130695
|
FINISHED |
| Object | more realistic 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: more realistic motifs | Statement: [Kaga yuzen dyeing, differenceFromKyoYuzen, more realistic motifs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: differenceFromKyoYuzen Context triple: [Kaga yuzen dyeing, differenceFromKyoYuzen, more realistic motifs]
-
A.
designDifferenceFrom
chosen
Indicates a relationship where one design is distinguished from another by specific differing features, characteristics, or structure.
-
B.
ichinomiya
Indicates a relationship where a location or institution holds the status of "Ichinomiya," the primary or highest-ranking Shinto shrine of a historical province.
-
C.
differIn
Indicates that two entities are not the same in at least one specified aspect, attribute, or value.
-
D.
isDifferenceOf
Indicates that one quantity or entity represents the result obtained by subtracting one specified quantity or entity from another.
-
E.
distanceToKyushu
Indicates the spatial distance between a given entity’s location and the region of Kyushu.
- 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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622b26848819098a558a4baf592fa |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:16 a.m.