Triple
T8600849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Illerkirchberg |
E203669
|
entity |
| Predicate | hasMayor |
P185
|
FINISHED |
| Object |
Markus Häußler
Markus Häußler is a German local politician who serves as the mayor of the municipality of Illerkirchberg in Baden-Württemberg.
|
E748409
|
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: Markus Häußler | Statement: [Illerkirchberg, hasMayor, Markus Häußler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markus Häußler Context triple: [Illerkirchberg, hasMayor, Markus Häußler]
-
A.
Markus Häußler
Markus Häußler is a German local politician who serves as the mayor of the town of Munderkingen in Baden-Württemberg.
-
B.
Markus Vogt
Markus Vogt is an architect known for his work on the design of the Bundesplatz in Switzerland.
-
C.
Andreas Scholz
Andreas Scholz is a person known for bearing the surname Scholz, though no widely recognized public profile or specific notable achievements are clearly associated with him from the given information.
-
D.
Christoph Dolle
Christoph Dolle is a German local politician who serves as the mayor of the town of Blomberg.
-
E.
Tobias Fünke
Tobias Fünke is a socially awkward, aspiring actor and former analyst-therapist known for his oblivious behavior and unintentional double entendres in the television series "Arrested Development."
- 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: Markus Häußler Triple: [Illerkirchberg, hasMayor, Markus Häußler]
Generated description
Markus Häußler is a German local politician who serves as the mayor of the municipality of Illerkirchberg in Baden-Württemberg.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Markus Häußler Target entity description: Markus Häußler is a German local politician who serves as the mayor of the municipality of Illerkirchberg in Baden-Württemberg.
-
A.
Markus Häußler
Markus Häußler is a German local politician who serves as the mayor of the town of Munderkingen in Baden-Württemberg.
-
B.
Markus Vogt
Markus Vogt is an architect known for his work on the design of the Bundesplatz in Switzerland.
-
C.
Andreas Scholz
Andreas Scholz is a person known for bearing the surname Scholz, though no widely recognized public profile or specific notable achievements are clearly associated with him from the given information.
-
D.
Christoph Dolle
Christoph Dolle is a German local politician who serves as the mayor of the town of Blomberg.
-
E.
Tobias Fünke
Tobias Fünke is a socially awkward, aspiring actor and former analyst-therapist known for his oblivious behavior and unintentional double entendres in the television series "Arrested Development."
- 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_69ca832b56948190ba751cec255308f1 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46d8ff408190acc7cd8dc99b2689 |
completed | March 31, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cecc839cdc819093c3cd0e44f173a2 |
completed | April 2, 2026, 8:07 p.m. |
| NEDg | Description generation | batch_69cece14193081909e7b36f5b5b7da40 |
completed | April 2, 2026, 8:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cecee1db28819095f704b96b8c6d2a |
completed | April 2, 2026, 8:17 p.m. |
Created at: March 30, 2026, 6:24 p.m.