Triple
T64304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of Belgium |
E1277
|
entity |
| Predicate | scriptUsedForMotto |
P4410
|
FINISHED |
| Object | Latin alphabet |
—
|
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: Latin alphabet | Statement: [Coat of arms of Belgium, scriptUsedForMotto, Latin alphabet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scriptUsedForMotto Context triple: [Coat of arms of Belgium, scriptUsedForMotto, Latin alphabet]
-
A.
mottoType
Indicates the specific category or kind of motto that characterizes the relationship between an entity and its motto.
-
B.
motto
Indicates that one entity serves as the guiding phrase, slogan, or maxim associated with another entity.
-
C.
formerMotto
Indicates that a motto was previously used by an entity but is no longer its current motto.
-
D.
translationOfMotto
Indicates that one motto is a translation of another motto in a different language.
-
E.
usedInPropaganda
Indicates that something is employed as a tool or element within propaganda efforts to influence opinions or behavior.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2516eda54819090f5c14384d4eab1 |
completed | Feb. 28, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69a24ea5c140819080409a968c8d2ce8 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a2516d98e88190b79261bd3fcadd9b |
completed | Feb. 28, 2026, 2:22 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.