Triple
T17303616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caroline Michaelis |
E420098
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Maulbronn |
—
|
NE NERFINISHED |
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: Maulbronn | Statement: [Caroline Michaelis, placeOfDeath, Maulbronn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maulbronn Context triple: [Caroline Michaelis, placeOfDeath, Maulbronn]
-
A.
Maulbronn
chosen
Maulbronn is a historic town in Baden-Württemberg, Germany, best known for its well-preserved medieval Cistercian monastery complex, a UNESCO World Heritage Site.
-
B.
Buhlbronn
Buhlbronn is a village-sized district of the town of Schorndorf in the German state of Baden-Württemberg.
-
C.
Waldbronn
Waldbronn is a municipality in the state of Baden-Württemberg in southwestern Germany, known for its spa facilities and proximity to the city of Karlsruhe.
-
D.
Blaubeuren
Blaubeuren is a historic town in the Alb-Donau district of Baden-Württemberg, Germany, known for its medieval old town and the karst spring Blautopf.
-
E.
Lautern
Lautern is a historical German locality known as the former residence of Palatine Count John Casimir of Simmern.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d886db32608190a61e18862c5a8af6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e438fc732481909065afddc5c687d4 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:41 a.m.