Triple
T5450812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artigas Mausoleum in Montevideo |
E122363
|
entity |
| Predicate | hasTypeOfGuard |
P48627
|
FINISHED |
| Object | ceremonial military guard |
—
|
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: ceremonial military guard | Statement: [Artigas Mausoleum in Montevideo, hasTypeOfGuard, ceremonial military guard]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfGuard Context triple: [Artigas Mausoleum in Montevideo, hasTypeOfGuard, ceremonial military guard]
-
A.
hasTypeOfCase
Indicates that an entity is associated with or classified under a particular type or category of case.
-
B.
hasGuardianFigureType
Indicates the type or role of a guardian figure associated with an entity.
-
C.
haveType
Indicates that an entity belongs to or is classified under a specified type or category.
-
D.
guardType
chosen
Indicates the specific kind or category of guarding role or protection associated with an entity.
-
E.
hasTypeOfNames
Indicates that one entity possesses or is associated with a particular category or kind of names defined by another entity.
- 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_69bd4640f52c81909e653ec361f66d76 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:07 p.m.