Triple
T8883049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bavarian State Chancellery |
E211456
|
entity |
| Predicate | reusesStructureOf |
P85513
|
FINISHED |
| Object | former Bavarian Army Museum |
—
|
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: former Bavarian Army Museum | Statement: [Bavarian State Chancellery, reusesStructureOf, former Bavarian Army Museum]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reusesStructureOf Context triple: [Bavarian State Chancellery, reusesStructureOf, former Bavarian Army Museum]
-
A.
usedStructure
Indicates that one entity makes use of, relies on, or operates through a particular structure (physical, logical, or organizational) to perform its function or action.
-
B.
replacedStructure
Indicates that one structure has been substituted for, or taken the place of, another structure.
-
C.
remainingStructuresUsedFor
Indicates that the remaining structures of an entity are utilized for a specified purpose or function.
-
D.
convertedStructureUse
Indicates that an entity’s original structural use has been changed to a different use or function.
-
E.
usesSameSubunitStructureAs
Indicates that two entities share an identical or equivalent arrangement and composition of their constituent subunits within a larger structural framework.
- 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_69ca838f9e20819096ab1f236a70381a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc616b2d988190b923ef1e33aab787 |
completed | April 1, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5d6e54808190af4156edd4c8ffbc |
completed | March 31, 2026, 11:49 p.m. |
Created at: March 30, 2026, 6:53 p.m.