Triple
T87863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puritanism |
E1765
|
entity |
| Predicate | viewOnEducation |
P4078
|
FINISHED |
| Object | literacy for Bible reading |
—
|
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: literacy for Bible reading | Statement: [Puritanism, viewOnEducation, literacy for Bible reading]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: viewOnEducation Context triple: [Puritanism, viewOnEducation, literacy for Bible reading]
-
A.
educationSystem
Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
-
B.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
C.
educates
Indicates that one entity provides instruction, knowledge, or training to another entity.
-
D.
educationalModel
Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of another entity.
-
E.
hasEducationalProgram
Indicates that an entity offers, runs, or is associated with a specific educational program.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2503d304c8190a0034ffa4a38a501 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb6da2c8190a33d144d219f7abe |
completed | Feb. 28, 2026, 2:11 a.m. |
| PDg | Predicate description generation | batch_69a2503c12808190a3cbb7b171f466f0 |
completed | Feb. 28, 2026, 2:17 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.