Triple
T27449373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberly Ellerth |
E692389
|
entity |
| Predicate | caseOutcomeLevel |
P71353
|
FINISHED |
| Object | U.S. Supreme Court review |
—
|
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: U.S. Supreme Court review | Statement: [Kimberly Ellerth, caseOutcomeLevel, U.S. Supreme Court review]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: caseOutcomeLevel Context triple: [Kimberly Ellerth, caseOutcomeLevel, U.S. Supreme Court review]
-
A.
legalOutcome
Indicates the resulting legal status, decision, or consequence that follows from a legal process, action, or judgment.
-
B.
outcomeType
Indicates the specific category or nature of the result produced by an event, process, or action.
-
C.
outcomeOf
Indicates that one entity is the result, consequence, or product that arises from another entity, event, or process.
-
D.
outcomeOfTrial
Indicates that a particular result or verdict is produced as the consequence of a specific trial or legal proceeding.
-
E.
hadCourtLevel
chosen
Indicates the specific hierarchical level of the court at which a legal case or judicial action took place.
- 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_69ef5206c9248190b5975c2a7f9d229c |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62dc4980481909e303ade433c7d61 |
completed | May 2, 2026, 5 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 12:47 p.m.