Triple
T10284344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clemens August of Bavaria |
E241188
|
entity |
| Predicate | placeOfDeath |
P21
|
FINISHED |
| Object | Brühl |
E727753
|
NE 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: Brühl | Statement: [Clemens August of Bavaria, placeOfDeath, Brühl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brühl Context triple: [Clemens August of Bavaria, placeOfDeath, Brühl]
-
A.
Brühl
chosen
Brühl is a German town in North Rhine-Westphalia known for its historic architecture and as the birthplace of surrealist artist Max Ernst.
-
B.
Lippendorf
Lippendorf is a village in Saxony, Germany, historically notable as the birthplace of Katharina von Bora, the wife of Martin Luther.
-
C.
Karlshagen
Karlshagen is a seaside resort village on the Baltic coast of northeastern Germany, located on the island of Usedom and known for its sandy beaches and tourism.
-
D.
Cölln
Cölln was a historic town on the River Spree that, together with Berlin, formed the core of what later became the city of Berlin.
-
E.
Seelingstädt
Seelingstädt is a village and subdivision of the town of Trebsen in the German state of Saxony.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2b5853081909cd0397e08a0f44d |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d0b40d081908eb3f7ba24352a42 |
completed | April 9, 2026, 3:29 a.m. |
Created at: April 6, 2026, 11:40 a.m.