Triple
T9349363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hofheim am Taunus |
E224974
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Christian Vogt
Christian Vogt is a German local politician who serves as the mayor of the town of Hofheim am Taunus in Hesse.
|
E792548
|
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: Christian Vogt | Statement: [Hofheim am Taunus, hasMayor, Christian Vogt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Vogt Context triple: [Hofheim am Taunus, hasMayor, Christian Vogt]
-
A.
Markus Vogt
Markus Vogt is an architect known for his work on the design of the Bundesplatz in Switzerland.
-
B.
Hannes Trautloft
Hannes Trautloft was a German Luftwaffe fighter ace and high-ranking officer during World War II who later became an important figure in the postwar West German Air Force.
-
C.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
-
D.
Peter Vinnemeier
Peter Vinnemeier is a German entrepreneur best known as a co-founder of the global hotel search and price comparison platform Trivago.
-
E.
Matthias Henne
Matthias Henne is a German local politician who serves as the mayor of the spa town Bad Waldsee in Baden-Württemberg.
- 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: Christian Vogt Triple: [Hofheim am Taunus, hasMayor, Christian Vogt]
Generated description
Christian Vogt is a German local politician who serves as the mayor of the town of Hofheim am Taunus in Hesse.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Christian Vogt Target entity description: Christian Vogt is a German local politician who serves as the mayor of the town of Hofheim am Taunus in Hesse.
-
A.
Markus Vogt
Markus Vogt is an architect known for his work on the design of the Bundesplatz in Switzerland.
-
B.
Hannes Trautloft
Hannes Trautloft was a German Luftwaffe fighter ace and high-ranking officer during World War II who later became an important figure in the postwar West German Air Force.
-
C.
Sven Wagner
Sven Wagner is a German local politician who serves as the mayor of the town of Aschersleben in Saxony-Anhalt.
-
D.
Peter Vinnemeier
Peter Vinnemeier is a German entrepreneur best known as a co-founder of the global hotel search and price comparison platform Trivago.
-
E.
Matthias Henne
Matthias Henne is a German local politician who serves as the mayor of the spa town Bad Waldsee in Baden-Württemberg.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f1198b88190adc0b01f7c1be36e |
completed | April 1, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0e43c31008190b542a9c5aa33f30e |
completed | April 4, 2026, 10:13 a.m. |
| NEDg | Description generation | batch_69d0e587586c8190a73ce417f0b5adec |
completed | April 4, 2026, 10:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0e5eb2ce88190973acc2cc8ce254f |
completed | April 4, 2026, 10:20 a.m. |
Created at: March 30, 2026, 7:41 p.m.