Triple
T2952883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huber |
E79860
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Bernd Huber
Bernd Huber is a German economist and academic who served as president of Ludwig Maximilian University of Munich.
|
E419116
|
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: Bernd Huber | Statement: [Huber, hasNotableBearer, Bernd Huber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bernd Huber Context triple: [Huber, hasNotableBearer, Bernd Huber]
-
A.
Karl Rammelt
Karl Rammelt was a German Luftwaffe fighter ace of World War II, credited with numerous aerial victories on the Eastern Front.
-
B.
Irmfried Eberl
Irmfried Eberl was an Austrian Nazi physician and SS officer who became the first commandant of the Treblinka extermination camp, playing a key role in the implementation of the Holocaust.
-
C.
Andreas Huber
Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
-
D.
Bruno Beger
Bruno Beger was a German SS anthropologist and war criminal involved in Nazi racial research and atrocities during World War II.
-
E.
Lutz Zülicke
Lutz Zülicke is a German physicist and academic best known for supervising Angela Merkel’s doctoral research in quantum chemistry.
- 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: Bernd Huber Triple: [Huber, hasNotableBearer, Bernd Huber]
Generated description
Bernd Huber is a German economist and academic who served as president of Ludwig Maximilian University of Munich.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bernd Huber Target entity description: Bernd Huber is a German economist and academic who served as president of Ludwig Maximilian University of Munich.
-
A.
Karl Rammelt
Karl Rammelt was a German Luftwaffe fighter ace of World War II, credited with numerous aerial victories on the Eastern Front.
-
B.
Irmfried Eberl
Irmfried Eberl was an Austrian Nazi physician and SS officer who became the first commandant of the Treblinka extermination camp, playing a key role in the implementation of the Holocaust.
-
C.
Andreas Huber
Andreas Huber is a relatively common German-speaking personal name shared by multiple individuals across fields such as sports, engineering, and the arts.
-
D.
Bruno Beger
Bruno Beger was a German SS anthropologist and war criminal involved in Nazi racial research and atrocities during World War II.
-
E.
Lutz Zülicke
Lutz Zülicke is a German physicist and academic best known for supervising Angela Merkel’s doctoral research in quantum chemistry.
- 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_69ad8b1276588190a374a0b12e0f7bdf |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad98fe4b688190a0f68c4f80cd6f8f |
completed | March 8, 2026, 3:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589aa20688190a74a65b0563c3938 |
completed | March 14, 2026, 4:15 p.m. |
| NEDg | Description generation | batch_69b58aa95428819085048691c77e2aea |
completed | March 14, 2026, 4:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b58b34c4e881909fd44fbe8acedda4 |
completed | March 14, 2026, 4:22 p.m. |
Created at: March 8, 2026, 2:57 p.m.