Triple
T17856838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena of Nassau-Dillenburg |
E445959
|
entity |
| Predicate | marriagePlace |
P128
|
FINISHED |
| Object | Dillenburg |
—
|
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: Dillenburg | Statement: [Magdalena of Nassau-Dillenburg, marriagePlace, Dillenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dillenburg Context triple: [Magdalena of Nassau-Dillenburg, marriagePlace, Dillenburg]
-
A.
Dillenburg
chosen
Dillenburg is a historic town in the German state of Hesse, known as the ancestral seat of the House of Orange-Nassau and its connection to Dutch history.
-
B.
Harbach
Harbach is a surname most notably associated with Otto Harbach, an American lyricist and librettist of early 20th-century musical theatre.
-
C.
Tecklenburg
Tecklenburg is a historic small town in North Rhine-Westphalia, Germany, known for its medieval architecture and open-air theater.
-
D.
Schwabhausen
Schwabhausen is a municipality in Bavaria, Germany, known for its rural character and location within the greater Munich metropolitan region.
-
E.
Warstein
Warstein is a town in North Rhine-Westphalia, Germany, best known for its Warsteiner brewery and its location in the Sauerland region.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4978bd5e081909e192f6aada5235f |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 10:17 a.m.