Triple
T36999706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shiro Lolita |
E915315
|
entity |
| Predicate | commonlyUsesFabric |
P135303
|
FINISHED |
| Object | lace |
—
|
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: lace | Statement: [Shiro Lolita, commonlyUsesFabric, lace]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonlyUsesFabric Context triple: [Shiro Lolita, commonlyUsesFabric, lace]
-
A.
typicalFabric
Indicates that something is made from or associated with a fabric material that is standard or characteristic for its type.
-
B.
hasFabric
chosen
Indicates that one entity is made of, incorporates, or is associated with a particular type of fabric.
-
C.
hasLiningMaterial
Indicates that one entity uses or contains another entity as the material forming its inner lining.
-
D.
fiberwiseDescription
Indicates a description or characterization that is given separately for each fiber in a fibered or parameterized structure, specifying how the relationship or action behaves over individual fibers.
-
E.
textileType
Indicates the specific kind or category of textile material associated with an entity.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff29d831b881908d485609e0fc1d0b |
completed | May 9, 2026, 12:34 p.m. |
| PD | Predicate disambiguation | batch_69ff28f9f9e4819087f3402735de66c7 |
completed | May 9, 2026, 12:30 p.m. |
Created at: May 3, 2026, 4:14 p.m.