Triple
T1567048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida courts |
E33454
|
entity |
| Predicate | numberOfCircuitCourts |
P4502
|
FINISHED |
| Object | 20 |
—
|
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: 20 | Statement: [Florida courts, numberOfCircuitCourts, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCircuitCourts Context triple: [Florida courts, numberOfCircuitCourts, 20]
-
A.
numberOfCourts
chosen
Indicates the quantity of courts associated with or present at a given entity or location.
-
B.
judicialCircuit
Indicates the judicial circuit within which a legal entity, case, or jurisdiction is organized or falls under authority.
-
C.
hasCourts
Indicates that an entity possesses, contains, or is equipped with one or more courts (e.g., legal, sports, or judicial facilities).
-
D.
numberOfJudges
Indicates the total count of judges associated with a particular case, event, or entity.
-
E.
hasBranchCourts
Indicates that an institution or main court maintains one or more subordinate or satellite courts under its 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_69a885f11b048190935025a035302715 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90fccd4b48190a44012888a00af7f |
completed | March 5, 2026, 5:08 a.m. |
| PD | Predicate disambiguation | batch_69a907b872f0819096b3df6ad502c63e |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.