Triple
T32513510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herschel Shmoikel Pinchas Yerucham Krustofsky |
E830997
|
entity |
| Predicate | faceMakeupColor |
P118236
|
FINISHED |
| Object | white (as Krusty) |
—
|
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: white (as Krusty) | Statement: [Herschel Shmoikel Pinchas Yerucham Krustofsky, faceMakeupColor, white (as Krusty)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceMakeupColor Context triple: [Herschel Shmoikel Pinchas Yerucham Krustofsky, faceMakeupColor, white (as Krusty)]
-
A.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
B.
fruitSkinColor
Indicates the color of the outer skin or peel of a fruit.
-
C.
facialMakeupIndicates
Indicates that the presence, style, or characteristics of facial makeup convey or signify a particular state, role, identity, or condition of an entity.
-
D.
hasFacePaintColor
chosen
Indicates that an entity’s face paint is of a specified color.
-
E.
facialDiscColor
Indicates the color or coloration pattern of an entity’s facial disc.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c4a08a888190b7a25f185dae36f8 |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1 a.m.