Triple
T9123582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Second Schröder cabinet |
E218917
|
entity |
| Predicate | containedOffice |
P11900
|
FINISHED |
| Object | Vice-Chancellor of Germany |
—
|
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: Vice-Chancellor of Germany | Statement: [Second Schröder cabinet, containedOffice, Vice-Chancellor of Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containedOffice Context triple: [Second Schröder cabinet, containedOffice, Vice-Chancellor of Germany]
-
A.
includedOffice
chosen
Indicates that one office is contained within, or forms part of, another office or organizational unit.
-
B.
controlledOffice
Indicates that one entity has authority over, manages, or directs the operations of a particular office or administrative location.
-
C.
officeIsIn
Indicates that one office is located within or inside another specified place or building.
-
D.
officeUnder
Indicates that one office is subordinate to, managed by, or organizationally within the authority of another office.
-
E.
officeIn
Indicates that one entity has an office located within the premises or jurisdiction of another entity.
- 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_69ca83dddd548190983b96c664f7f367 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cca8b5fa188190be6465e74cf26915 |
completed | April 1, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69cc66003e3c819091e1e42c9cf7c781 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:17 p.m.