Triple
T6760374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Feigl |
E154574
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Johann Feigl
Johann Feigl was an Austrian SS officer and war criminal active during the Nazi era.
|
E634101
|
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: Johann Feigl | Statement: [Feigl, hasNotableBearer, Johann Feigl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Johann Feigl Context triple: [Feigl, hasNotableBearer, Johann Feigl]
-
A.
Günther Feigl
Günther Feigl is a notable individual recognized as a prominent bearer of the surname Feigl.
-
B.
Fritz Feigl
Fritz Feigl was an Austrian-Brazilian chemist renowned as a pioneer of spot test analysis in analytical chemistry.
-
C.
Ernst Feigl
Ernst Feigl is an individual notable enough to be recognized as a significant bearer of the surname Feigl, though specific widely known biographical details about him are not clearly established.
-
D.
Peter Feigl
Peter Feigl is a former Austrian professional tennis player who competed on the international circuit in the 1970s and early 1980s.
-
E.
Friedrich Waismann
Friedrich Waismann was an Austrian mathematician, philosopher, and close collaborator of Ludwig Wittgenstein, known for his contributions to logical positivism and the philosophy of language.
- 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: Johann Feigl Triple: [Feigl, hasNotableBearer, Johann Feigl]
Generated description
Johann Feigl was an Austrian SS officer and war criminal active during the Nazi era.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Johann Feigl Target entity description: Johann Feigl was an Austrian SS officer and war criminal active during the Nazi era.
-
A.
Günther Feigl
Günther Feigl is a notable individual recognized as a prominent bearer of the surname Feigl.
-
B.
Fritz Feigl
Fritz Feigl was an Austrian-Brazilian chemist renowned as a pioneer of spot test analysis in analytical chemistry.
-
C.
Ernst Feigl
Ernst Feigl is an individual notable enough to be recognized as a significant bearer of the surname Feigl, though specific widely known biographical details about him are not clearly established.
-
D.
Peter Feigl
Peter Feigl is a former Austrian professional tennis player who competed on the international circuit in the 1970s and early 1980s.
-
E.
Friedrich Waismann
Friedrich Waismann was an Austrian mathematician, philosopher, and close collaborator of Ludwig Wittgenstein, known for his contributions to logical positivism and the philosophy of language.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d212c31881909dfe8ca9de69acf7 |
completed | March 27, 2026, 6:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c769e417788190a297b277ef0496ff |
completed | March 28, 2026, 5:40 a.m. |
| NEDg | Description generation | batch_69c76a67bb048190b9bff17d4da4d842 |
completed | March 28, 2026, 5:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76ac6d8b48190869e1733adcbd3d9 |
completed | March 28, 2026, 5:44 a.m. |
Created at: March 27, 2026, 2:12 p.m.