Triple
T17680620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | District of South Carolina |
E440757
|
entity |
| Predicate | hasNumberOfJudgeships |
P16419
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [District of South Carolina, hasNumberOfJudgeships, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfJudgeships Context triple: [District of South Carolina, hasNumberOfJudgeships, 10]
-
A.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
B.
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.
-
C.
hasMagistrateJudges
Indicates that one legal jurisdiction, court, or governing body includes or is served by one or more magistrate judges.
-
D.
hasJudges
Indicates that one entity serves as a judge or panel of judges for another entity, such as an event, competition, or legal case.
-
E.
hasNumberOfJudicialCircuits
Indicates the specific count of judicial circuits associated with an 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4704357b8819087e3a93e9eefd858 |
completed | April 19, 2026, 6:03 a.m. |
| PD | Predicate disambiguation | batch_69e3cde3673c8190a889e14ba1f07dc1 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 10:01 a.m.