Triple
T20729714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberwolfach |
E509536
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Matthias Bauernfeind
Matthias Bauernfeind is a German local politician who serves as the mayor of the municipality of Oberwolfach in Baden-Württemberg.
|
E1447474
|
NE FINISHED |
How this triple was built (4 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: Matthias Bauernfeind | Statement: [Oberwolfach, hasMayor, Matthias Bauernfeind]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matthias Bauernfeind Context triple: [Oberwolfach, hasMayor, Matthias Bauernfeind]
-
A.
Michael Hainisch
Michael Hainisch was an Austrian politician and statesman who served as the first democratically elected President of Austria in the early 20th century.
-
B.
Matthias Fleischer
Matthias Fleischer is a cinematographer best known for his work on the 2015 film adaptation of "Heidi."
-
C.
Matthias Butz
Matthias Butz is an individual notable enough to be specifically cited as a bearer of the surname Butz.
-
D.
Matthias Koenigswieser
Matthias Koenigswieser is a cinematographer known for his work on feature films such as the live-action Disney movie "Christopher Robin."
-
E.
John Rädecker
John Rädecker was a Dutch sculptor best known for his expressive, symbolist-influenced monumental works in the early 20th century.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Matthias Bauernfeind Triple: [Oberwolfach, hasMayor, Matthias Bauernfeind]
Generated description
Matthias Bauernfeind is a German local politician who serves as the mayor of the municipality of Oberwolfach in Baden-Württemberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Matthias Bauernfeind Target entity description: Matthias Bauernfeind is a German local politician who serves as the mayor of the municipality of Oberwolfach in Baden-Württemberg.
-
A.
Michael Hainisch
Michael Hainisch was an Austrian politician and statesman who served as the first democratically elected President of Austria in the early 20th century.
-
B.
Matthias Fleischer
Matthias Fleischer is a cinematographer best known for his work on the 2015 film adaptation of "Heidi."
-
C.
Matthias Butz
Matthias Butz is an individual notable enough to be specifically cited as a bearer of the surname Butz.
-
D.
Matthias Koenigswieser
Matthias Koenigswieser is a cinematographer known for his work on feature films such as the live-action Disney movie "Christopher Robin."
-
E.
John Rädecker
John Rädecker was a Dutch sculptor best known for his expressive, symbolist-influenced monumental works in the early 20th century.
- F. None of above. chosen
Provenance (5 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1eb5d44819082d9fa410e676d91 |
completed | April 21, 2026, 12:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08e05db8ac8190bd2e7ca0d184a426 |
completed | May 16, 2026, 9:23 p.m. |
| NEDg | Description generation | batch_6a08e15d93ec8190bbe859fb42a4a5ac |
completed | May 16, 2026, 9:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08e25d8cb08190ba75b792aac192ab |
completed | May 16, 2026, 9:32 p.m. |
Created at: April 16, 2026, 12:30 p.m.