Triple
T14124539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Fürstenberg |
E339993
|
entity |
| Predicate | traditionalSeat |
P16984
|
FINISHED |
| Object | Donaueschingen |
E453611
|
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: Donaueschingen | Statement: [House of Fürstenberg, traditionalSeat, Donaueschingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donaueschingen Context triple: [House of Fürstenberg, traditionalSeat, Donaueschingen]
-
A.
Donaueschingen
chosen
Donaueschingen is a town in southwestern Germany, in the Black Forest region of Baden-Württemberg, known as one of the sources of the Danube River.
-
B.
Metzingen
Metzingen is a town in the German state of Baden-Württemberg, known for its Swabian heritage and large outlet shopping district.
-
C.
Elchingen
Elchingen is a municipality in southern Germany, historically notable as the site of a major Napoleonic victory during the War of the Third Coalition.
-
D.
Schwäbisch Gmünd
Schwäbisch Gmünd is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and long tradition of metalworking and jewelry craftsmanship.
-
E.
Offenburg
Offenburg is a city in southwestern Germany’s Baden-Württemberg state, known as a regional economic and transport hub near the French border in the Upper Rhine region.
- 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_69d81c6a95b481909e39111e0c1f31ee |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de6096976481909dc79066c5165a50 |
completed | April 14, 2026, 3:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b38823881909c9df93371782b47 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 9, 2026, 10:22 p.m.