Triple
T1989537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | László Löwenstein |
E43219
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Löwenstein |
E43219
|
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: Löwenstein | Statement: [László Löwenstein, familyName, Löwenstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Löwenstein Context triple: [László Löwenstein, familyName, Löwenstein]
-
A.
Löwenstein
chosen
Löwenstein is the original family name of the renowned Hungarian-American actor Peter Lorre, known for his distinctive roles in classic Hollywood and European cinema.
-
B.
Löhr
Löhr is a German-language surname borne by various notable individuals, including figures in military, arts, and public life.
-
C.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
-
D.
Lahnstein
Lahnstein is a historic town in western Germany, located on the Rhine River in the state of Rhineland-Palatinate.
-
E.
Neubukow
Neubukow is a small town in northern Germany best known as the birthplace of archaeologist Heinrich Schliemann.
- 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_69a88714cf2c819081644be450b8356e |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8434cec819087842e2c9537df9e |
completed | March 7, 2026, 5:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae0ad7c254819091159c5362e7a293 |
completed | March 8, 2026, 11:48 p.m. |
Created at: March 4, 2026, 7:37 p.m.