Triple
T13375038
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidential Standard of Kenya |
E319161
|
entity |
| Predicate | hasDifferentDesignsFor |
P109666
|
FINISHED |
| Object | different presidents of Kenya |
—
|
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: different presidents of Kenya | Statement: [Presidential Standard of Kenya, hasDifferentDesignsFor, different presidents of Kenya]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDifferentDesignsFor Context triple: [Presidential Standard of Kenya, hasDifferentDesignsFor, different presidents of Kenya]
-
A.
hasDifferentFrontDesigns
Indicates that the related entities possess distinct or non-identical designs on their front sides.
-
B.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
C.
designsFor
Indicates that one entity creates or plans something specifically intended to serve, suit, or be used by another entity.
-
D.
hasDesignOption
Indicates that an entity is associated with or offers a particular design alternative or configurable design choice.
-
E.
hasDesignChange
Indicates that an entity has undergone a modification or alteration to its original design.
- 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_69d806b886bc8190b676e7768b8e01c5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dadcda64a48190b53243a763cd175b |
completed | April 11, 2026, 11:44 p.m. |
| PD | Predicate disambiguation | batch_69d9a02c9abc8190b328e7bae747bfc5 |
completed | April 11, 2026, 1:13 a.m. |
| PDg | Predicate description generation | batch_69dadcce5a808190847f2a7833b67a5a |
completed | April 11, 2026, 11:44 p.m. |
Created at: April 9, 2026, 9:33 p.m.