Triple
T25784525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blakely v. Washington |
E649383
|
entity |
| Predicate | appliesRuleFrom |
P6249
|
FINISHED |
| Object | Apprendi v. New Jersey |
E649382
|
NE 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: Apprendi v. New Jersey | Statement: [Blakely v. Washington, appliesRuleFrom, Apprendi v. New Jersey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesRuleFrom Context triple: [Blakely v. Washington, appliesRuleFrom, Apprendi v. New Jersey]
-
A.
usesRulesFrom
chosen
Indicates that one entity applies, follows, or is governed by the rules defined or provided by another entity.
-
B.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
C.
enforcesRule
Indicates that one entity compels or ensures that another entity follows or complies with a specified rule or set of rules.
-
D.
basedOnRule
Indicates that something is determined, derived, or decided according to a specified rule or set of rules.
-
E.
hasRuleFor
Indicates that one entity defines or applies a rule that governs or constrains another entity or situation.
- F. None of above.
Provenance (4 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_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a10cc27eb988190805fa2cf0de534a1 |
completed | May 22, 2026, 9:35 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 22, 2026, 5:53 a.m.