Triple
T23781637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavarian crown |
E587829
|
entity |
| Predicate | locatedInSymbolicContext |
P153911
|
FINISHED |
| Object | Bavarian state symbols |
—
|
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: Bavarian state symbols | Statement: [Bavarian crown, locatedInSymbolicContext, Bavarian state symbols]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInSymbolicContext Context triple: [Bavarian crown, locatedInSymbolicContext, Bavarian state symbols]
-
A.
locatedInEventContext
Indicates that an entity exists or occurs within the situational, spatial, or temporal context defined by a particular event.
-
B.
hasSymbolLocation
Indicates that a symbol is associated with or positioned at a specific location.
-
C.
namedInContextOf
Indicates that an entity is mentioned or identified specifically within a particular context, situation, or frame of reference.
-
D.
containsSymbolicAct
Indicates that one entity includes or incorporates a symbolic action or gesture associated with another entity.
-
E.
mountSymbolizes
Indicates that a mount (such as a horse, vehicle, or rideable creature) serves as a symbolic representation of something else, such as status, role, or affiliation.
- 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_69e2490f4ad48190b690878eec3596c6 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1c62d7c608190b5fd0cf35f5faf42 |
completed | April 29, 2026, 8:49 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
| PDg | Predicate description generation | batch_69f15ed138f88190a8ae555422978908 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 17, 2026, 7:16 p.m.