Triple
T10886747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katherina Hedwig Pringsheim |
E257067
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Katia Mann |
E49287
|
NE FINISHED |
How this triple was built (2 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: Katia Mann | Statement: [Katherina Hedwig Pringsheim, alsoKnownAs, Katia Mann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Katia Mann Context triple: [Katherina Hedwig Pringsheim, alsoKnownAs, Katia Mann]
-
A.
Katia Mann
chosen
Katia Mann was a German intellectual and the wife and close confidante of Nobel Prize–winning author Thomas Mann, known for her significant influence on his life and work.
-
B.
Katia Behrens
Katia Behrens is a notable individual who bears the surname Behrens, recognized for her significance among people with that name.
-
C.
Astrid Eckert
Astrid Eckert is a historian and academic known for her work on modern German history, memory culture, and the legacy of the Cold War.
-
D.
Meret Becker
Meret Becker is a German actress and singer known for her versatile performances in film, television, and theater.
-
E.
Hildegard Knef
Hildegard Knef was a renowned German actress and singer, celebrated for her postwar film roles and distinctive, smoky-voiced chanson performances.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751dea1a88190b916879be8d74413 |
completed | April 9, 2026, 7:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7ecf1c48190aef0d31ef03d1f88 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 8, 2026, 9:21 p.m.