Triple
T4771980
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German presidential election, 1925 |
E105947
|
entity |
| Predicate | predecessorInOfficeStatus |
P34201
|
FINISHED |
| Object | died in office in 1925 |
—
|
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: died in office in 1925 | Statement: [German presidential election, 1925, predecessorInOfficeStatus, died in office in 1925]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorInOfficeStatus Context triple: [German presidential election, 1925, predecessorInOfficeStatus, died in office in 1925]
-
A.
predecessorInOffice
chosen
Indicates that one officeholder directly held a particular position before another officeholder in an official succession.
-
B.
successorOfficeTo
Indicates that one office or position directly follows and replaces another in an official sequence or hierarchy.
-
C.
predecessorInOfficeOfVictim
Indicates that the subject held a particular office or position immediately before the victim did.
-
D.
successorOfficeHolder
Indicates that one office holder directly follows another in occupying the same official position.
-
E.
precededByOfficeHolder
Indicates that one office holder directly held a position before another office holder in a sequence of occupants of the same office.
- 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_69bd43f226fc8190b867cc249c2a9042 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd655e5dcc8190a932be9b1baaffb2 |
completed | March 20, 2026, 3:18 p.m. |
| PD | Predicate disambiguation | batch_69bd6229d8448190a271719e5e30fd82 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:21 p.m.