Triple
T2789098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max Löwenthal |
E61882
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Löwenthal |
E46160
|
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: Löwenthal | Statement: [Max Löwenthal, familyName, Löwenthal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löwenthal Context triple: [Max Löwenthal, familyName, Löwenthal]
-
A.
Löwenthal
chosen
Löwenthal is the maiden surname of Elsa Einstein, who was both the second wife and cousin of physicist Albert Einstein.
-
B.
Rosenbad
Rosenbad is a prominent government building complex in central Stockholm that houses the offices of the Prime Minister and the Swedish Government.
-
C.
Heurich
Heurich is a German surname most notably associated with Christian Heurich, a prominent brewer and businessman in Washington, D.C.
-
D.
Kuppenheimer
Kuppenheimer was a prominent American men's clothing company best known for its high-quality suits and influential early 20th-century advertising campaigns.
-
E.
Miltenberg
Miltenberg is a historic town in Bavaria, Germany, known for its well-preserved medieval old town along the Main River and its timber-framed architecture.
- 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_69ab4b7f51d881908768300ebd2fbdae |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddb3d63c8190b3ab5fa363c69db8 |
completed | March 7, 2026, 8:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afc6589558819088442f09db328dac |
completed | March 10, 2026, 7:20 a.m. |
Created at: March 6, 2026, 9:58 p.m.