Triple
T14578673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nannette Streicher |
E342126
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Streicher |
E78876
|
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: Streicher | Statement: [Nannette Streicher, familyName, Streicher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Streicher Context triple: [Nannette Streicher, familyName, Streicher]
-
A.
Streicher
chosen
Streicher is a German surname most infamously associated with Julius Streicher, a prominent Nazi propagandist and publisher of the antisemitic newspaper Der Stürmer.
-
B.
Stradner
Stradner is a surname most notably associated with Austrian-American actress Rosa Stradner.
-
C.
Stottlemeyer
Stottlemeyer is the surname of Captain Leland Stottlemeyer, a central police character from the television series "Monk."
-
D.
Estreicher
Estreicher is a Polish family name most notably associated with Karol Estreicher Sr., a prominent 19th-century bibliographer and historian of Polish literature.
-
E.
Kreuzer
The Kreuzer was a small silver coin and monetary unit used for centuries in various German-speaking states within the Holy Roman Empire and beyond.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f6f78c81908a30ecb4c025299d |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94b832b08190965b727baa700403 |
completed | May 8, 2026, 7:46 a.m. |
Created at: April 10, 2026, 1:24 a.m.