Triple
T25625962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heads of the Proposals |
E642429
|
entity |
| Predicate | proposedReformOf |
P125760
|
FINISHED |
| Object | religious settlement |
—
|
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: religious settlement | Statement: [Heads of the Proposals, proposedReformOf, religious settlement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: proposedReformOf Context triple: [Heads of the Proposals, proposedReformOf, religious settlement]
-
A.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
-
B.
subjectToReformBy
Indicates that an entity is undergoing or designated for changes, improvements, or restructuring carried out by another entity.
-
C.
advocatedReformOf
chosen
Indicates that one entity publicly supported or promoted changes to another entity, typically aiming to improve or modify its structure, policies, or practices.
-
D.
isPartOfReform
Indicates that an action, measure, or component belongs to, contributes to, or is included within a broader reform initiative or process.
-
E.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
- 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_69e77e7bd4548190a0c691b8a2f27ff1 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 5:14 p.m.