Triple
T22621567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dr. Susan Lowenstein |
E558294
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lowenstein |
—
|
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: Lowenstein | Statement: [Dr. Susan Lowenstein, familyName, Lowenstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lowenstein Context triple: [Dr. Susan Lowenstein, familyName, Lowenstein]
-
A.
Lowenstein
chosen
Lowenstein is a surname of German origin, often associated with Jewish families and various notable individuals in fields such as politics, academia, and the arts.
-
B.
Bronstein
Bronstein is the original family surname of the Russian revolutionary leader Leon Trotsky.
-
C.
Arnstein
Arnstein is a town in the Mansfeld-Südharz district of Saxony-Anhalt, Germany, formed through the merger of several smaller municipalities.
-
D.
Orenstein & Koppel
Orenstein & Koppel was a German engineering company best known for manufacturing locomotives, rail vehicles, and heavy industrial machinery in the late 19th and 20th centuries.
-
E.
Waterstein
Waterstein is a small coastal settlement on the Duirinish peninsula of the Isle of Skye in Scotland, known for its dramatic cliffs and proximity to Neist Point.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f16e39959481909e0ae67379435f95 |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 3 p.m.