Triple
T7094059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke Power Company |
E165275
|
entity |
| Predicate | legalRoleInCase |
P16985
|
FINISHED |
| Object | defendant in Griggs v. Duke Power Co. |
—
|
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: defendant in Griggs v. Duke Power Co. | Statement: [Duke Power Company, legalRoleInCase, defendant in Griggs v. Duke Power Co.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalRoleInCase Context triple: [Duke Power Company, legalRoleInCase, defendant in Griggs v. Duke Power Co.]
-
A.
legalCaseRole
chosen
Indicates the specific role or capacity an entity holds within a legal case, such as plaintiff, defendant, judge, or attorney.
-
B.
legalSystemRole
Indicates the specific function, capacity, or position an entity holds within a legal or judicial system.
-
C.
roleAtCourt
Indicates the specific position, function, or status an entity holds within a court or courtly setting.
-
D.
legalProfessionRole
Indicates that one entity holds or performs a specific professional role within the legal domain in relation to another entity or context.
-
E.
courtRole
Indicates the specific capacity or position an entity holds within a court proceeding or judicial context.
- 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_69c6887e8c10819091cee237560d32da |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e55159848190a794ad77e60c5525 |
completed | March 27, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c172148190bf290c07bf579d1f |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:41 p.m.