Triple
T8351097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feldherrnhalle |
E196158
|
entity |
| Predicate | hadMemorial |
P501
|
FINISHED |
| Object | Nazi-era Ehrentempel nearby |
—
|
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: Nazi-era Ehrentempel nearby | Statement: [Feldherrnhalle, hadMemorial, Nazi-era Ehrentempel nearby]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMemorial Context triple: [Feldherrnhalle, hadMemorial, Nazi-era Ehrentempel nearby]
-
A.
hasMemorial
chosen
Indicates that a memorial exists in honor of, or dedicated to, a particular entity.
-
B.
memorialization
Indicates the act of preserving the memory or honoring the legacy of someone or something, often through a dedicated object, event, or practice.
-
C.
hasAdjacentMemorial
Indicates that one memorial is located directly next to or in close proximity to another memorial.
-
D.
hasGraveOrMemorialOf
Indicates that a location or object serves as the grave or memorial site dedicated to a particular person or entity.
-
E.
memorialType
Indicates the specific kind or category of memorial associated with an entity (e.g., plaque, statue, monument).
- 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_69ca82edd63c8190b876b8465464c5fa |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8019fb308190a3edc744bd473a5b |
completed | March 31, 2026, 8:04 a.m. |
| PD | Predicate disambiguation | batch_69cb70c6d0ec8190acf273b0e007b51a |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 5:59 p.m.