Triple
T36059958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank the Rabbit |
E1043047
|
entity |
| Predicate | maskMaterialAppearance |
P184526
|
FINISHED |
| Object | metallic skull-like rabbit face |
—
|
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: metallic skull-like rabbit face | Statement: [Frank the Rabbit, maskMaterialAppearance, metallic skull-like rabbit face]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maskMaterialAppearance Context triple: [Frank the Rabbit, maskMaterialAppearance, metallic skull-like rabbit face]
-
A.
maskColor
Indicates the color attribute associated with a mask.
-
B.
maskStyle
Indicates the style or design characteristics of a mask used or worn in the described context.
-
C.
maskMaterialTradition
Indicates a relationship where a mask is associated with, or originates from, a particular material tradition or customary way of making masks.
-
D.
maskDecoration
Indicates that one entity serves as a decorative element or embellishment applied to a mask.
-
E.
materialVariant
Indicates that one entity is a version or variation of another entity distinguished by differences in material composition.
- 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_69f76e2f09448190b0486d5ecad5e243 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b35e32d481909ef0220e6f6ff4a8 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1bad2e88190963ab4ee5d4f2038 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2c66054819083897e25edb65ba7 |
completed | May 3, 2026, 8:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.