Triple
T6943428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jagdgeschwader 54 |
E160733
|
entity |
| Predicate | notableCommander |
P1197
|
FINISHED |
| Object |
Anton Mader
Anton Mader was a German Luftwaffe fighter ace and officer during World War II, known for his leadership roles on the Eastern Front.
|
E637981
|
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: Anton Mader | Statement: [Jagdgeschwader 54, notableCommander, Anton Mader]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anton Mader Context triple: [Jagdgeschwader 54, notableCommander, Anton Mader]
-
A.
Peter Riedler
Peter Riedler is an Austrian academic and university administrator who serves as rector of the University of Graz.
-
B.
Paul Krendler
Paul Krendler is a corrupt and antagonistic U.S. Justice Department official who serves as a key foil to Clarice Starling in the film "Hannibal."
-
C.
Johann Hohenstein
Johann Hohenstein was an early 16th-century printer known for producing works by the English Bible translator William Tyndale.
-
D.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
E.
Hugo Matuschek
Hugo Matuschek is the demanding but ultimately kind-hearted owner of a Budapest leather goods shop in the classic romantic comedy film "The Shop Around the Corner."
- 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: Anton Mader Triple: [Jagdgeschwader 54, notableCommander, Anton Mader]
Generated description
Anton Mader was a German Luftwaffe fighter ace and officer during World War II, known for his leadership roles on the Eastern Front.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Anton Mader Target entity description: Anton Mader was a German Luftwaffe fighter ace and officer during World War II, known for his leadership roles on the Eastern Front.
-
A.
Peter Riedler
Peter Riedler is an Austrian academic and university administrator who serves as rector of the University of Graz.
-
B.
Paul Krendler
Paul Krendler is a corrupt and antagonistic U.S. Justice Department official who serves as a key foil to Clarice Starling in the film "Hannibal."
-
C.
Johann Hohenstein
Johann Hohenstein was an early 16th-century printer known for producing works by the English Bible translator William Tyndale.
-
D.
Markus Morgenstern
Markus Morgenstern is a mathematician known for his contributions to combinatorics and graph theory.
-
E.
Hugo Matuschek
Hugo Matuschek is the demanding but ultimately kind-hearted owner of a Budapest leather goods shop in the classic romantic comedy film "The Shop Around the Corner."
- 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da876c9c8190996f3ff84858e8d1 |
completed | March 27, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7882e3cfc81909ca7ecf507ac9adc |
completed | March 28, 2026, 7:50 a.m. |
| NEDg | Description generation | batch_69c7891785288190974db0bca4b8f265 |
completed | March 28, 2026, 7:53 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c78982bc308190aeffc3f786a82327 |
completed | March 28, 2026, 7:55 a.m. |
Created at: March 27, 2026, 2:28 p.m.