Triple
T36576285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Errol Childress |
E902260
|
entity |
| Predicate | decoratesWith |
P38145
|
FINISHED |
| Object | twig sculptures |
—
|
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: twig sculptures | Statement: [Errol Childress, decoratesWith, twig sculptures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: decoratesWith Context triple: [Errol Childress, decoratesWith, twig sculptures]
-
A.
decoratedFor
Indicates that an entity has received a decoration, award, or honor in recognition of a specific action, service, or achievement.
-
B.
decoratedOn
Indicates that one entity has been adorned, embellished, or ornamented on a specific date, occasion, or point in time.
-
C.
hasDecor
chosen
Indicates that one entity possesses, features, or is adorned with a particular decorative element or style.
-
D.
décorateur
Indicates that one entity serves as a decorator for another, typically enhancing or modifying its appearance, style, or presentation.
-
E.
decoratedMember
Indicates that an entity has been formally honored or awarded, typically for notable service, achievement, or distinction.
- 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_69f76e64d8908190868473959a250b94 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.