Triple
T25950216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serena Southerlyn |
E653947
|
entity |
| Predicate | legalSide |
P8814
|
FINISHED |
| Object | prosecution |
—
|
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: prosecution | Statement: [Serena Southerlyn, legalSide, prosecution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalSide Context triple: [Serena Southerlyn, legalSide, prosecution]
-
A.
legalRepresentation
chosen
Indicates that one entity formally acts on behalf of another in legal matters, such as providing counsel, advocacy, or defense within a legal system.
-
B.
legalBackground
Indicates that an entity has education, training, or experience related to law or the legal profession.
-
C.
legalMatters
Indicates that one entity is involved with, concerned about, or responsible for legal issues, processes, or obligations related to another entity or context.
-
D.
legalView
Indicates that one entity holds or expresses a legal opinion, interpretation, or judgment about another entity or situation.
-
E.
legalTool
Indicates a relationship where something functions as a legal instrument, mechanism, or means used to achieve or regulate a legal purpose or outcome.
- 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_69e7ab40ac788190a771bc499eb1ae5f |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 22, 2026, 8:43 a.m.