Triple
T4367111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samuel Holdheim |
E98802
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Samuel Holdheim |
E98802
|
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: Samuel Holdheim | Statement: [Samuel Holdheim, name, Samuel Holdheim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Samuel Holdheim Context triple: [Samuel Holdheim, name, Samuel Holdheim]
-
A.
Samuel Holdheim
chosen
Samuel Holdheim was a pioneering 19th-century German rabbi and theologian who became one of the most radical and influential leaders of early Reform Judaism.
-
B.
Samuel Fischer
Samuel Fischer was a prominent German publisher best known for founding the influential S. Fischer Verlag, which played a key role in modern German literature.
-
C.
Samuel Weiss
Samuel Weiss is a relatively obscure individual whose specific public significance is not clearly established from the available information.
-
D.
Josias Philip Hoffman
Josias Philip Hoffman was a 19th-century South African politician who served as the first State President of the Orange Free State.
-
E.
Moritz Borman
Moritz Borman is a film producer known for working on major Hollywood productions, including the science fiction action film "Terminator Salvation."
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35201be7081908808e81634060f95 |
completed | March 12, 2026, 11:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5e50838188190b5b698d4bd2b5784 |
completed | March 14, 2026, 10:45 p.m. |
Created at: March 12, 2026, 11:17 p.m.