Triple
T18522286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isabella Rossellini |
E452616
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Jonathan Wiedemann |
—
|
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: Jonathan Wiedemann | Statement: [Isabella Rossellini, spouse, Jonathan Wiedemann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jonathan Wiedemann Context triple: [Isabella Rossellini, spouse, Jonathan Wiedemann]
-
A.
Jonathan Wiedemann
chosen
Jonathan Wiedemann is a former model and the ex-husband of Italian actress and model Isabella Rossellini.
-
B.
Stefen Fangmeier
Stefen Fangmeier is a visual effects supervisor and film director best known for directing the fantasy film "Eragon."
-
C.
Chris Weinke
Chris Weinke is a former American football quarterback best known for leading Florida State University to a national championship and winning the Heisman Trophy before playing in the NFL.
-
D.
Ken Schretzmann
Ken Schretzmann is a film editor known for his work on major animated features, including Guillermo del Toro's stop-motion adaptation of Pinocchio.
-
E.
Justin Neudecker
Justin Neudecker is a character associated with Hammad, likely appearing in the same narrative or creative work.
- 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5338e6e188190a41a4ee12c1ad330 |
completed | April 19, 2026, 7:57 p.m. |
Created at: April 10, 2026, 11:37 a.m.