Triple
T16813765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. federal courts |
E408685
|
entity |
| Predicate | hasNumberOfRegionalCircuits |
P26350
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [U.S. federal courts, hasNumberOfRegionalCircuits, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfRegionalCircuits Context triple: [U.S. federal courts, hasNumberOfRegionalCircuits, 13]
-
A.
numberOfCircuits
Indicates the total count of circuits associated with or contained in a given entity or system.
-
B.
numberOfCircuitsInSystem
chosen
Indicates the total count of circuits that exist within a given system.
-
C.
hasNumberOfJudicialCircuits
Indicates the specific count of judicial circuits associated with an entity.
-
D.
regionalsNumber
Indicates the number of regional-level instances (such as events, competitions, or units) associated with an entity.
-
E.
numberOfCourts
Indicates the quantity of courts associated with or present at a given entity or location.
- 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_69d88394566c8190b3dcbdc72935f7fa |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b2e01fb8819081cf2c08f29448da |
completed | April 18, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69e32b814b188190aee525f8779203cd |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:23 a.m.