Triple
T11834149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mainz 05 |
E281471
|
entity |
| Predicate | chairman |
P377
|
FINISHED |
| Object |
Stefan Hofmann
Stefan Hofmann is a German football executive best known for serving as the chairman of Bundesliga club 1. FSV Mainz 05.
|
E1103917
|
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: Stefan Hofmann | Statement: [Mainz 05, chairman, Stefan Hofmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stefan Hofmann Context triple: [Mainz 05, chairman, Stefan Hofmann]
-
A.
Stefan Menzel
Stefan Menzel is a person notable enough to be specifically distinguished among individuals sharing the surname Menzel.
-
B.
Andreas Fuchs
Andreas Fuchs is a German local politician who serves as the mayor of the town of Plattling in Bavaria.
-
C.
Stefan Metzger
Stefan Metzger is a notable individual recognized as a prominent bearer of the Metzger surname.
-
D.
Stefan Lucks
Stefan Lucks is a cryptographer known for his research in symmetric-key cryptography, hash functions, and contributions to the design and analysis of modern cryptographic algorithms.
-
E.
Andreas Stegemann
Andreas Stegemann is a German local politician who serves as the mayor of the city of Recklinghausen in North Rhine-Westphalia.
- 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: Stefan Hofmann Triple: [Mainz 05, chairman, Stefan Hofmann]
Generated description
Stefan Hofmann is a German football executive best known for serving as the chairman of Bundesliga club 1. FSV Mainz 05.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Stefan Hofmann Target entity description: Stefan Hofmann is a German football executive best known for serving as the chairman of Bundesliga club 1. FSV Mainz 05.
-
A.
Stefan Menzel
Stefan Menzel is a person notable enough to be specifically distinguished among individuals sharing the surname Menzel.
-
B.
Andreas Fuchs
Andreas Fuchs is a German local politician who serves as the mayor of the town of Plattling in Bavaria.
-
C.
Stefan Metzger
Stefan Metzger is a notable individual recognized as a prominent bearer of the Metzger surname.
-
D.
Stefan Lucks
Stefan Lucks is a cryptographer known for his research in symmetric-key cryptography, hash functions, and contributions to the design and analysis of modern cryptographic algorithms.
-
E.
Andreas Stegemann
Andreas Stegemann is a German local politician who serves as the mayor of the city of Recklinghausen in North Rhine-Westphalia.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62e7e408190998bebe346c82e89 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a2796cc81908b6d4cf71f39e88a |
completed | May 8, 2026, 5:52 a.m. |
| NEDg | Description generation | batch_69fd7cb98ba08190bddf0656c44e8d4e |
completed | May 8, 2026, 6:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd7d58e5308190a1352d1698ddb58b |
completed | May 8, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:43 p.m.