Triple
T7167271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edwards v. Aguillard |
E167101
|
entity |
| Predicate | findsEffect |
P75247
|
FINISHED |
| Object | advances a particular religious belief |
—
|
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: advances a particular religious belief | Statement: [Edwards v. Aguillard, findsEffect, advances a particular religious belief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: findsEffect Context triple: [Edwards v. Aguillard, findsEffect, advances a particular religious belief]
-
A.
finds
Indicates that one entity discovers, locates, or comes upon another entity, often as the result of a search or encounter.
-
B.
eventEffect
Indicates the resulting change, outcome, or consequence that one event has on another state, entity, or event.
-
C.
usesEffectType
Indicates that an entity employs or is associated with a particular type or category of effect in its operation or behavior.
-
D.
hasEffectNamedAfter
Indicates that an entity has an effect or phenomenon that is named after another entity.
-
E.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
- F. None of above. chosen
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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85b4410819098c6531229da51d4 |
completed | March 27, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
| PDg | Predicate description generation | batch_69c6e4a213508190a40aca39f9eee7d5 |
completed | March 27, 2026, 8:12 p.m. |
Created at: March 27, 2026, 2:48 p.m.