Triple
T1704817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Constitutional Court of Germany |
E36847
|
entity |
| Predicate | numberOfSenates |
P32457
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Federal Constitutional Court of Germany, numberOfSenates, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSenates Context triple: [Federal Constitutional Court of Germany, numberOfSenates, 2]
-
A.
numberOfSenators
Indicates the total count of senators associated with a given political body, region, or entity.
-
B.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
C.
representedInSenate
Indicates that an entity serves as a representative for another entity within a senate or upper legislative chamber.
-
D.
totalNumberOfLegislators
Indicates the total count of legislators associated with a given political body, jurisdiction, or legislative session.
-
E.
numberOfCommitteeMembers
Indicates the total count of individuals who are members of a given committee.
- 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_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. |
| PDg | Predicate description generation | batch_69ab75ac1408819086b22b3cd0672a79 |
completed | March 7, 2026, 12:47 a.m. |
Created at: March 4, 2026, 7:30 p.m.