Triple
T21593886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flag of Malaysia |
E532846
|
entity |
| Predicate | starPointCount |
P7181
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [Flag of Malaysia, starPointCount, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starPointCount Context triple: [Flag of Malaysia, starPointCount, 14]
-
A.
starPointRepresents
Indicates that a specific star point symbol or marker is used to represent or denote another entity, feature, or value.
-
B.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
-
C.
hasNumberOfPoints
chosen
Indicates that an entity is associated with a specific count of points it possesses or comprises.
-
D.
leafPoints
Indicates that one leaf or leaf-like structure is oriented or directed toward, or points at, another entity.
-
E.
numberOfPointSources
Indicates the total count of distinct point sources involved or present in a given context or system.
- 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_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. |
Created at: April 16, 2026, 6:32 p.m.