Triple
T27379790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Stephen of Lorraine |
E691185
|
entity |
| Predicate | startTime (Grand Duke of Tuscany) |
P29471
|
FINISHED |
| Object | 1737 |
—
|
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: 1737 | Statement: [Francis Stephen of Lorraine, startTime (Grand Duke of Tuscany), 1737]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime (Grand Duke of Tuscany) Context triple: [Francis Stephen of Lorraine, startTime (Grand Duke of Tuscany), 1737]
-
A.
startTime (Duke of Bavaria)
Indicates the point in time at which the person began holding the title or office of Duke of Bavaria.
-
B.
endTime (Grand Duke of Tuscany)
Indicates the point in time at which the tenure or reign of the Grand Duke of Tuscany comes to an end.
-
C.
startTime (Grand Princess of Tuscany)
Indicates the point in time at which the event or state associated with the Grand Princess of Tuscany begins.
-
D.
startTime (Duke of Saxony)
Indicates the point in time at which the individual became the Duke of Saxony.
-
E.
reignAsGrandDukeOfTuscanyStart
chosen
Indicates the time at which an individual begins their tenure as Grand Duke of Tuscany.
- 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_69ef52022538819081f873d0c84a6dd6 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 27, 2026, 12:22 p.m.