Triple
T7731145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vasily Stalin |
E175256
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Maria Nuzberg |
E175256
|
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: Maria Nuzberg | Statement: [Vasily Stalin, spouse, Maria Nuzberg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maria Nuzberg Context triple: [Vasily Stalin, spouse, Maria Nuzberg]
-
A.
Maria Nuzberg
chosen
Maria Nuzberg was the wife of Vasily Stalin, the son of Soviet leader Joseph Stalin.
-
B.
Margaret Shenberg
Margaret Shenberg was the first wife of influential Hollywood film producer and studio executive Louis B. Mayer.
-
C.
Margot Löwenthal
Margot Löwenthal was the daughter of Elsa Löwenthal, who was Albert Einstein’s second wife and cousin.
-
D.
Jane Rosenthal
Jane Rosenthal is an American film producer and co-founder of Tribeca Productions and the Tribeca Film Festival, known for her long-time collaboration with Robert De Niro on numerous high-profile films.
-
E.
Helene Shapiro
Helene Shapiro is an American mathematician known for her work in linear algebra and matrix theory, and as a student of Olga Taussky-Todd.
- 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_69c6995e912c81909a49a2657103f786 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70336aafc819099a060950ab8922f |
completed | March 27, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8f30c099081909aaeac321fbf0066 |
completed | March 29, 2026, 9:38 a.m. |
Created at: March 27, 2026, 4:06 p.m.