Triple
T25784526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blakely v. Washington |
E649383
|
entity |
| Predicate | extendsPrecedent |
P9926
|
FINISHED |
| Object | Apprendi v. New Jersey |
—
|
NE NERFINISHED |
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: Apprendi v. New Jersey | Statement: [Blakely v. Washington, extendsPrecedent, Apprendi v. New Jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: extendsPrecedent Context triple: [Blakely v. Washington, extendsPrecedent, Apprendi v. New Jersey]
-
A.
modifiedPrecedent
Indicates that one entity has altered, qualified, or changed the terms, scope, or interpretation of a prior decision, rule, or precedent.
-
B.
extendedInCase
Indicates that one entity is lengthened, prolonged, or expanded when a particular condition or case applies.
-
C.
precedentFor
Indicates that one situation, decision, or case serves as an authoritative example or basis for deciding or interpreting another.
-
D.
typicalPrecedent
Indicates that one situation, case, or event serves as a standard or commonly followed example for how similar later situations are handled.
-
E.
extendedBy
chosen
Indicates that one entity builds upon, enlarges, or adds to the scope, functionality, or duration of another entity.
- 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_69e7ab33e9308190afe415dc6f9e8876 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60c3b09488190ade1b69ff7f0df0e |
completed | May 2, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f60b8461ac81908c5bd3d73eed59f4 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 22, 2026, 5:53 a.m.