Triple
T37219185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commissioner Bele |
E922827
|
entity |
| Predicate | skinColorPattern |
P153670
|
FINISHED |
| Object | black on the right side of his body and white on the left side |
—
|
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: black on the right side of his body and white on the left side | Statement: [Commissioner Bele, skinColorPattern, black on the right side of his body and white on the left side]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skinColorPattern Context triple: [Commissioner Bele, skinColorPattern, black on the right side of his body and white on the left side]
-
A.
skinColorDescription
chosen
Indicates a descriptive characterization of an entity’s skin color.
-
B.
hasFacialSkinColor
Indicates that one entity has a specific facial skin color characterized or attributed by another entity.
-
C.
fruitSkinColor
Indicates the color of the outer skin or peel of a fruit.
-
D.
hasFleshColor
Indicates that an entity possesses a particular color or characteristic of its flesh or internal tissue.
-
E.
fleshColor
Indicates the color or hue of an entity’s flesh or skin.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.