Triple
T23471018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena Scholl |
E570126
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Scholl |
E561844
|
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: Scholl | Statement: [Magdalena Scholl, familyName, Scholl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scholl Context triple: [Magdalena Scholl, familyName, Scholl]
-
A.
Scholl
chosen
Scholl is the surname of Sophie Scholl, the German student and anti-Nazi resistance member known for her role in the White Rose movement during World War II.
-
B.
Scholl
Scholl is a well-known foot care brand offering products such as insoles, treatments for common foot conditions, and comfort footwear.
-
C.
Jergens
Jergens is a surname most notably associated with American actress Diane Jergens.
-
D.
Nivea
Nivea is an American R&B singer best known for her early-2000s hits like "Don't Mess with My Man" and collaborations with prominent hip-hop artists.
-
E.
Lifebuoy
Lifebuoy is a long-established global soap and hygiene brand known for its antibacterial products and health-focused marketing.
- 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_69e245af8a88819084f2704f6d265a92 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a6ff8dc0819086961b1f07030d9c |
completed | April 29, 2026, 6:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c825dcbdc819090002d36ef823a2f |
completed | May 19, 2026, 3:31 p.m. |
Created at: April 17, 2026, 5:55 p.m.