Triple
T10738516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aimée & Jaguar |
E253257
|
entity |
| Predicate | plotSummary |
P264
|
FINISHED |
| Object | portrays a forbidden love affair between a Jewish woman and the wife of a Nazi officer in wartime Berlin |
—
|
LITERAL FINISHED |
How this triple was built (1 step)
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: portrays a forbidden love affair between a Jewish woman and the wife of a Nazi officer in wartime Berlin | Statement: [Aimée & Jaguar, plotSummary, portrays a forbidden love affair between a Jewish woman and the wife of a Nazi officer in wartime Berlin]
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_69d6aa5e51e8819095f06881cecf152e |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d710424d8c81908ee9b59d622f2af5 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:14 p.m.