Triple
T3037263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron Karl Schlosser |
E83040
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Mercedes Jellinek |
E83040
|
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: Mercedes Jellinek | Statement: [Baron Karl Schlosser, spouse, Mercedes Jellinek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mercedes Jellinek Context triple: [Baron Karl Schlosser, spouse, Mercedes Jellinek]
-
A.
Mercedes Jellinek
chosen
Mercedes Jellinek was the daughter of automobile entrepreneur Emil Jellinek and the namesake of the Mercedes brand of luxury cars.
-
B.
Marianne Ehrlich
Marianne Ehrlich was the daughter of Nobel Prize–winning German physician and immunologist Paul Ehrlich.
-
C.
Elisabeth Binzenstock
Elisabeth Binzenstock was the wife of the renowned German Renaissance painter Hans Holbein the Younger.
-
D.
Margarete Boden
Margarete Boden was a German nurse who became known as the wife of Heinrich Himmler, one of the leading figures of Nazi Germany.
-
E.
Anna Eberstein
Anna Eberstein is a Swedish television producer and retail executive best known as the wife of British actor Hugh Grant.
- 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_69ad8b2298908190a7cb4e9bdbf064d0 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2cd4988190b52fe3616ecbe9ef |
completed | March 8, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f86cfcac81908122f1afd79ce29a |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:01 p.m.