Triple
T26775627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida Bar Examination |
E670111
|
entity |
| Predicate | subjectAreaTested |
P63100
|
FINISHED |
| Object | Florida constitutional 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: Florida constitutional law | Statement: [Florida Bar Examination, subjectAreaTested, Florida constitutional law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectAreaTested Context triple: [Florida Bar Examination, subjectAreaTested, Florida constitutional law]
-
A.
subjectAreaLevel
Indicates the hierarchical level or depth of specialization of a particular subject area in relation to others.
-
B.
examContentArea
chosen
Indicates that an exam includes or focuses on a particular content area or subject domain.
-
C.
assessmentAreaDefinedBy
Indicates that the scope or domain of an assessment is specified or delimited by a particular area or boundary.
-
D.
competenceArea
Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
-
E.
primarySubjectArea
Indicates the main academic or topical field to which something (such as a work, course, or resource) is most centrally related.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 27, 2026, 4:04 a.m.