Triple
T24171550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elisabeth Katharina Christine |
E599147
|
entity |
| Predicate | officeEndForRegency |
P155575
|
FINISHED |
| Object | 1741-12-06 |
—
|
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: 1741-12-06 | Statement: [Elisabeth Katharina Christine, officeEndForRegency, 1741-12-06]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: officeEndForRegency Context triple: [Elisabeth Katharina Christine, officeEndForRegency, 1741-12-06]
-
A.
officeEndTimeFor
Indicates the time at which an entity’s office hours or work period end for another specified entity.
-
B.
officeEnded
Indicates that a person’s term in an office or position has concluded at a specified time or under certain conditions.
-
C.
officeEndApproximate
Indicates that an office or term ended around an approximate date rather than on a precisely known day.
-
D.
officeEndTime (RNC Chair)
Indicates the time at which the RNC Chair’s term in office concludes.
-
E.
previousOfficeEndTime
Indicates the time at which an entity’s immediately preceding office or position ended.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
| PDg | Predicate description generation | batch_69f27a753ca8819095706970d368f762 |
completed | April 29, 2026, 9:39 p.m. |
Created at: April 17, 2026, 11:33 p.m.