Triple
T27167909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Federal Criminal Court of Switzerland |
E682825
|
entity |
| Predicate | seatDeterminedBy |
P92113
|
FINISHED |
| Object | federal law |
—
|
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: federal law | Statement: [Federal Criminal Court of Switzerland, seatDeterminedBy, federal law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatDeterminedBy Context triple: [Federal Criminal Court of Switzerland, seatDeterminedBy, federal law]
-
A.
seatOn
Indicates that one entity is positioned or placed on a seat or seating surface associated with another entity.
-
B.
seatIs
Indicates that one entity functions as the seat or seating position of another entity.
-
C.
seatSince
Indicates that an entity has held a particular seat, position, or place continuously since a specified point in time.
-
D.
seatDesignatedBy
chosen
Indicates that a specific seat has been assigned or allocated to an entity by a particular agent or authority.
-
E.
seatNumber
Indicates the specific numbered position assigned to a seat within a defined seating arrangement or venue.
- 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_69eefacf6e788190a75a64399d9e3109 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f625451be88190b9b2c24b3d50e09c |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 9:22 a.m.