Triple
T3694670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Wittmann |
E78427
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Wittmann
Wittmann is a German surname borne by various notable individuals across fields such as military history, sports, and academia.
|
E379717
|
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: Wittmann | Statement: [Michael Wittmann, familyName, Wittmann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wittmann Context triple: [Michael Wittmann, familyName, Wittmann]
-
A.
Mölders
Mölders is a German surname most prominently associated with World War II Luftwaffe fighter ace Werner Mölders.
-
B.
Dietrich Stobbe
Dietrich Stobbe was a German Social Democratic politician who served as the Governing Mayor of West Berlin during the late 1970s and early 1980s.
-
C.
Heinsohn
Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
-
D.
Gütermann
Gütermann is a German surname most notably associated with the Gütermann family involved in industry and manufacturing, particularly in the production of sewing threads.
-
E.
Mennekes
Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
- 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: Wittmann Triple: [Michael Wittmann, familyName, Wittmann]
Generated description
Wittmann is a German surname borne by various notable individuals across fields such as military history, sports, and academia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wittmann Target entity description: Wittmann is a German surname borne by various notable individuals across fields such as military history, sports, and academia.
-
A.
Mölders
Mölders is a German surname most prominently associated with World War II Luftwaffe fighter ace Werner Mölders.
-
B.
Dietrich Stobbe
Dietrich Stobbe was a German Social Democratic politician who served as the Governing Mayor of West Berlin during the late 1970s and early 1980s.
-
C.
Heinsohn
Heinsohn is a surname most prominently associated with Tom Heinsohn, a Hall of Fame Boston Celtics player, coach, and broadcaster.
-
D.
Gütermann
Gütermann is a German surname most notably associated with the Gütermann family involved in industry and manufacturing, particularly in the production of sewing threads.
-
E.
Mennekes
Mennekes is a German electrical engineering company best known in e-mobility for developing the widely adopted Type 2 AC charging connector for electric vehicles.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4eafd348190986f69aee787fd8f |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3d0f2d88190b31e8c336f1a1bf3 |
completed | March 14, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69b4c5280d788190b59b23acf5f77811 |
completed | March 14, 2026, 2:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c58b13c48190b975e61000aa1f05 |
completed | March 14, 2026, 2:18 a.m. |
Created at: March 8, 2026, 3:26 p.m.