Triple
T12416237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stille Hilfe |
E296642
|
entity |
| Predicate | notableCaseSupported |
P95555
|
FINISHED |
| Object | Walter Reder |
E909728
|
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: Walter Reder | Statement: [Stille Hilfe, notableCaseSupported, Walter Reder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Walter Reder Context triple: [Stille Hilfe, notableCaseSupported, Walter Reder]
-
A.
Walter Reder
chosen
Walter Reder was an Austrian SS officer and war criminal notorious for leading brutal anti-partisan operations in Italy during World War II.
-
B.
Walter Blum
Walter Blum is a German mathematician known for his contributions to algebra and mathematical education.
-
C.
Walter Naegle
Walter Naegle is an American activist and archivist best known as the longtime partner and estate executor of civil rights leader Bayard Rustin.
-
D.
Walter Wottitz
Walter Wottitz was a French cinematographer best known for his Academy Award-winning work on the World War II epic film "The Longest Day."
-
E.
Walter Trarbach
Walter Trarbach is a theatrical sound designer known for his work on major Broadway productions, including SpongeBob SquarePants: The Broadway Musical.
- 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_69d6ad9f464c81909db36d7e96e34b9e |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541ace208190a5149b6f18fa196d |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9db383cc8190b1c65d202785838a |
completed | May 9, 2026, 2:36 a.m. |
Created at: April 8, 2026, 9:55 p.m.