Triple
T16013080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Violante Beatrix of Bavaria |
E388389
|
entity |
| Predicate | startTime (Grand Princess of Tuscany) |
P121362
|
FINISHED |
| Object | 1689 |
—
|
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: 1689 | Statement: [Violante Beatrix of Bavaria, startTime (Grand Princess of Tuscany), 1689]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime (Grand Princess of Tuscany) Context triple: [Violante Beatrix of Bavaria, startTime (Grand Princess of Tuscany), 1689]
-
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.
startTime (Duke of Saxony)
Indicates the point in time at which the individual became the Duke of Saxony.
-
C.
startTime (Empress of Mexico)
Indicates the point in time at which the reign or tenure of the Empress of Mexico began.
-
D.
startTime (as Duchess of Brittany)
Indicates the point in time when an individual began serving in the role of Duchess of Brittany.
-
E.
startTime (Governor of Victoria)
Indicates the point in time at which someone begins serving as Governor of Victoria.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e1826a4f7c8190aba6d4f1075141b0 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e185879c10819080a18e24969b5a6d |
completed | April 17, 2026, 12:57 a.m. |
Created at: April 10, 2026, 4:55 a.m.