Triple
T19625879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lessing J. Rosenwald |
E471132
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Rosenwald |
—
|
NE NERFINISHED |
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: Rosenwald | Statement: [Lessing J. Rosenwald, familyName, Rosenwald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosenwald Context triple: [Lessing J. Rosenwald, familyName, Rosenwald]
-
A.
Carnegie
Carnegie is a Scottish surname most famously associated with industrialist and philanthropist Andrew Carnegie.
-
B.
Julius Rosenwald
chosen
Julius Rosenwald was an American businessman and philanthropist best known for leading Sears, Roebuck & Co. and funding thousands of schools for African American children in the rural South.
-
C.
Higginbotham
Higginbotham is the married surname of Renée Dwyer, a character from Stephenie Meyer’s Twilight series.
-
D.
Swasey
Swasey is a surname of English origin borne by various notable individuals, including architects, politicians, and academics.
-
E.
Lessing J. Rosenwald
Lessing J. Rosenwald was an American businessman, art collector, and philanthropist renowned for his extensive collection of rare books and prints, much of which he donated to the Library of Congress and the National Gallery of Art.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e510fa248190b7afb274a1d4cf73 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e640e9ff208190afb33c910ed2147b |
completed | April 20, 2026, 3:06 p.m. |
Created at: April 10, 2026, 1:44 p.m.