Triple
T287815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Royal Military Academy (Belgium) |
E5922
|
entity |
| Predicate | hasMottoType |
P504
|
FINISHED |
| Object | military academy motto |
—
|
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: military academy motto | Statement: [Royal Military Academy (Belgium), hasMottoType, military academy motto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMottoType Context triple: [Royal Military Academy (Belgium), hasMottoType, military academy motto]
-
A.
mottoType
chosen
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.
scriptUsedForMotto
Indicates that a particular writing system or script is used to render or express a given motto.
-
D.
hasTypeOfInsignia
Indicates that an entity bears or is associated with a specific kind or category of insignia.
-
E.
languageOfMotto
Indicates the language in which a motto is written or expressed.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a25e2ddaa88190b08c40b5823f30a0 |
completed | Feb. 28, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69a25b7c1448819082064f474633acd5 |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.