Triple
T21243435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Carolina Code of Laws (as amended) |
E523540
|
entity |
| Predicate | subjectIncludes |
P450
|
FINISHED |
| Object | criminal law of South Carolina |
—
|
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: criminal law of South Carolina | Statement: [South Carolina Code of Laws (as amended), subjectIncludes, criminal law of South Carolina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectIncludes Context triple: [South Carolina Code of Laws (as amended), subjectIncludes, criminal law of South Carolina]
-
A.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
B.
subjectMatter
chosen
Indicates the topic, theme, or content area that something (such as a work, document, or discussion) is about.
-
C.
subjectCategories
Indicates that an entity is associated with one or more subject-based categories or classifications.
-
D.
subjectGroup
Indicates that an entity functions as a group or collection that the subject belongs to or is categorized under.
-
E.
subjectOfWork
Indicates that one entity is the main topic, focus, or theme that a particular work (such as a book, article, or artwork) is about.
- 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_69e0b513b89c81908b27147e91368db2 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7352507448190ba1f14cef16d69be |
completed | April 21, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f61239708190ab7b3c83ae848a0d |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:47 p.m.