Triple
T1704819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Constitutional Court of Germany |
E36847
|
entity |
| Predicate | eachSenateHasJudges |
P16419
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [Federal Constitutional Court of Germany, eachSenateHasJudges, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eachSenateHasJudges Context triple: [Federal Constitutional Court of Germany, eachSenateHasJudges, 8]
-
A.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
B.
hasJudiciary
Indicates that an entity possesses, is served by, or is under the authority of a judicial body or legal court system.
-
C.
hasJudge
Indicates that a legal case, proceeding, or decision is presided over or decided by a particular judge.
-
D.
numberOfSupremeCourtJustices
Indicates the total count of individuals serving as justices on a specified Supreme Court.
-
E.
authorizedJudgeships
chosen
Indicates the number or set of judicial positions that are officially established and permitted by law or authority for a given court or jurisdiction.
- 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_69a88617439c819094ffb5d16a0f6307 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69ab75ad24408190814069e6e3ef9e59 |
completed | March 7, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69aa61bad17c8190861b92cfb423f68f |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.