Triple
T539742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eva Braun |
E12602
|
entity |
| Predicate | subsequentFateOfRemains |
P14555
|
FINISHED |
| Object | exhumed and repeatedly reburied by Soviet authorities |
—
|
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: exhumed and repeatedly reburied by Soviet authorities | Statement: [Eva Braun, subsequentFateOfRemains, exhumed and repeatedly reburied by Soviet authorities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subsequentFateOfRemains Context triple: [Eva Braun, subsequentFateOfRemains, exhumed and repeatedly reburied by Soviet authorities]
-
A.
burialPlace
Indicates the location where a person or entity is buried.
-
B.
placeOfDeath
Indicates the location where an entity (typically a person or animal) died.
-
C.
numberOfBurials
chosen
Indicates the total count of burial events associated with a given entity.
-
D.
cremationPlace
Indicates the place where a person or entity was cremated.
-
E.
hasNotableBurials
Indicates that a place, typically a cemetery or burial site, contains the graves or remains of individuals considered notable or significant.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4985e51908190a34aa82ea9dbee1e |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b67c308190a1a225ab7c4b74c6 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.