Triple
T15657151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph the Reformer |
E376470
|
entity |
| Predicate | significantReformArea |
P88043
|
FINISHED |
| Object | administration |
—
|
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: administration | Statement: [Joseph the Reformer, significantReformArea, administration]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: significantReformArea Context triple: [Joseph the Reformer, significantReformArea, administration]
-
A.
reformsArea
chosen
Indicates that an entity is responsible for changing, improving, or restructuring a particular area or domain.
-
B.
notableReform
Indicates that an entity is recognized for having initiated, led, or been central to a significant reform or transformative change in a system, policy, or institution.
-
C.
relatedReforms
Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
-
D.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
E.
associatedReforms
Indicates a relationship where certain reforms are linked or connected to a given entity, such as a policy, event, or individual.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef3cb8c8190a10815b675b341c1 |
completed | April 16, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69deda890140819082608931e993dd61 |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:15 a.m.