Triple

T9851210
Position Surface form Disambiguated ID Type / Status
Subject Ingo E239471 entity
Predicate hasNotableBearer P458 FINISHED
Object Ingo Zamperoni
Ingo Zamperoni is a German journalist and television presenter best known as one of the main anchors of the ARD news program "Tagesthemen."
E828762 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: Ingo Zamperoni | Statement: [Ingo, hasNotableBearer, Ingo Zamperoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ingo Zamperoni
Context triple: [Ingo, hasNotableBearer, Ingo Zamperoni]
  • A. Dario Hübner
    Dario Hübner is a former Italian striker renowned for his prolific goal-scoring in Serie A well into his thirties, particularly with provincial clubs.
  • B. Uli Meyer
    Uli Meyer is a German-born animator and illustrator known for his character design and animation work in film and advertising.
  • C. Bruno Beger
    Bruno Beger was a German SS anthropologist and war criminal involved in Nazi racial research and atrocities during World War II.
  • D. Jörg Winger
    Jörg Winger is a German television producer and writer best known as the co-creator of the acclaimed Cold War spy drama series *Deutschland 83/86/89*.
  • E. Manfred Morari
    Manfred Morari is a prominent control systems engineer known for his pioneering work in model predictive control and contributions to robust and constrained control theory.
  • 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: Ingo Zamperoni
Triple: [Ingo, hasNotableBearer, Ingo Zamperoni]
Generated description
Ingo Zamperoni is a German journalist and television presenter best known as one of the main anchors of the ARD news program "Tagesthemen."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ingo Zamperoni
Target entity description: Ingo Zamperoni is a German journalist and television presenter best known as one of the main anchors of the ARD news program "Tagesthemen."
  • A. Dario Hübner
    Dario Hübner is a former Italian striker renowned for his prolific goal-scoring in Serie A well into his thirties, particularly with provincial clubs.
  • B. Uli Meyer
    Uli Meyer is a German-born animator and illustrator known for his character design and animation work in film and advertising.
  • C. Bruno Beger
    Bruno Beger was a German SS anthropologist and war criminal involved in Nazi racial research and atrocities during World War II.
  • D. Jörg Winger
    Jörg Winger is a German television producer and writer best known as the co-creator of the acclaimed Cold War spy drama series *Deutschland 83/86/89*.
  • E. Manfred Morari
    Manfred Morari is a prominent control systems engineer known for his pioneering work in model predictive control and contributions to robust and constrained control theory.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3742fe48190bae6e6d828a9cc0d completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20d511e348190aab23a45048ea7b3 completed April 5, 2026, 7:20 a.m.
NEDg Description generation batch_69d20e9f480c819086b0165aa77ddb06 completed April 5, 2026, 7:26 a.m.
NED2 Entity disambiguation (via description) batch_69d20fa9cab88190bbddcf18b49f8172 completed April 5, 2026, 7:30 a.m.
Created at: March 30, 2026, 8:34 p.m.