Triple
T2139686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tobias Nipkow |
E46732
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object |
Markus Wenzel
Markus Wenzel is a computer scientist best known as the primary developer of the Isabelle proof assistant.
|
E238249
|
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 Wenzel | Statement: [Tobias Nipkow, notableStudent, Markus Wenzel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markus Wenzel Context triple: [Tobias Nipkow, notableStudent, Markus Wenzel]
-
A.
Gilles Dowek
Gilles Dowek is a French logician and computer scientist known for his influential work in proof theory, type systems, and automated deduction.
-
B.
Johannes Eisermann
Johannes Eisermann is a scholar known for his professorship at the European University Viadrina in Frankfurt (Oder), where he has made notable academic contributions.
-
C.
Tobias Nipkow
Tobias Nipkow is a German computer scientist known for his influential work in interactive theorem proving and formal verification, particularly through his contributions to the Isabelle proof assistant.
-
D.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
E.
Harald Ganzinger
Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
- 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 Wenzel Triple: [Tobias Nipkow, notableStudent, Markus Wenzel]
Generated description
Markus Wenzel is a computer scientist best known as the primary developer of the Isabelle proof assistant.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Markus Wenzel Target entity description: Markus Wenzel is a computer scientist best known as the primary developer of the Isabelle proof assistant.
-
A.
Gilles Dowek
Gilles Dowek is a French logician and computer scientist known for his influential work in proof theory, type systems, and automated deduction.
-
B.
Johannes Eisermann
Johannes Eisermann is a scholar known for his professorship at the European University Viadrina in Frankfurt (Oder), where he has made notable academic contributions.
-
C.
Tobias Nipkow
Tobias Nipkow is a German computer scientist known for his influential work in interactive theorem proving and formal verification, particularly through his contributions to the Isabelle proof assistant.
-
D.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
E.
Harald Ganzinger
Harald Ganzinger was a prominent German computer scientist known for his influential work in automated theorem proving and term rewriting systems.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbe025d3c81908bcb33a7ff09eae8 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51b1290c8190a08850b428c99a6c |
completed | March 9, 2026, 4:50 a.m. |
| NEDg | Description generation | batch_69ae55923b748190bf7a2df3ae94edc8 |
completed | March 9, 2026, 5:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae55fdc32c8190b6ecdc9b23d64cc5 |
completed | March 9, 2026, 5:09 a.m. |
Created at: March 4, 2026, 7:44 p.m.