Triple
T17479997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stone v. Graham |
E425630
|
entity |
| Predicate | foundPrimaryEffect |
P1634
|
FINISHED |
| Object | advancement of religion |
—
|
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: advancement of religion | Statement: [Stone v. Graham, foundPrimaryEffect, advancement of religion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: foundPrimaryEffect Context triple: [Stone v. Graham, foundPrimaryEffect, advancement of religion]
-
A.
primaryEffect
chosen
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
B.
findsEffect
Indicates that one entity discovers, identifies, or determines the effect or outcome produced by another entity.
-
C.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
D.
measuredEffect
Indicates that an action or process has produced a specific, quantified outcome or impact on something.
-
E.
providesEffect
Indicates that one entity causes, delivers, or produces a particular effect or outcome on 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451bf1e8081909f4d4b8992412e62 |
completed | April 19, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f341c88190adabe526d8903b05 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:48 a.m.