Triple
T21593738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Kazakhstan |
E532843
|
entity |
| Predicate | featuresSun |
P144094
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Flag of Kazakhstan, featuresSun, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresSun Context triple: [Flag of Kazakhstan, featuresSun, true]
-
A.
featuresSuit
Indicates that one entity includes or presents a particular suit (e.g., clothing, armor, or outfit) as a notable component or attribute.
-
B.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
featuresStar
Indicates that one entity prominently includes or showcases another entity as a main star or featured performer.
-
D.
featuresMode
Indicates that one entity operates in, supports, or is characterized by a particular mode or configuration specified by another entity.
-
E.
featuresCross
Indicates that one feature or element intersects or passes across another in space or structure.
- 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_69e0c46251648190876f0427cf2d321b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eefadf6e608190b42b26ea22c76ec6 |
completed | April 27, 2026, 5:57 a.m. |
| PD | Predicate disambiguation | batch_69e632109d048190b4ac3f14fe48d1a0 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e63384a8fc819084c596bb53a3a1db |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 16, 2026, 6:32 p.m.