Triple
T14451148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Lorraine in Tuscany |
E358336
|
entity |
| Predicate | periodOfMajorReforms |
P50931
|
FINISHED |
| Object | 18th century |
—
|
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: 18th century | Statement: [House of Lorraine in Tuscany, periodOfMajorReforms, 18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: periodOfMajorReforms Context triple: [House of Lorraine in Tuscany, periodOfMajorReforms, 18th century]
-
A.
timeOfMajorReforms
chosen
Indicates the specific time period during which significant reforms or major changes took place.
-
B.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
C.
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.
-
D.
lastReform
Indicates the most recent reform or change that was applied to an entity, typically linking the entity to its latest reform event or version.
-
E.
survivedReformsOf
Indicates that one entity continued to exist or remain in its role despite reforms, changes, or restructuring initiated by 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de916244948190bb09d1bfc485ba50 |
completed | April 14, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69de5c3a02fc819097373f97a260cdeb |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:19 a.m.