Triple
T14930008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivan Alekseyevich |
E372234
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Praskovia Saltykova |
E97009
|
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: Praskovia Saltykova | Statement: [Ivan Alekseyevich, spouse, Praskovia Saltykova]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Praskovia Saltykova Context triple: [Ivan Alekseyevich, spouse, Praskovia Saltykova]
-
A.
Praskovia Saltykova
chosen
Praskovia Saltykova was a Russian noblewoman and tsarevna consort best known as the wife of Tsar Ivan V and the mother of Empress Anna of Russia.
-
B.
Martha Apraksina
Martha Apraksina was a Russian noblewoman best known as the second wife of Tsar Feodor III of Russia.
-
C.
Nadezhda Vasilyeva
Nadezhda Vasilyeva is known primarily as a daughter of Vasily Stalin, the son of Soviet leader Joseph Stalin.
-
D.
Nadezhda Vasilyeva
Nadezhda Vasilyeva is a costume designer known for her work on the film "Two Women."
-
E.
Lyubov Belozerskaya
Lyubov Belozerskaya was the second wife of Russian writer Mikhail Bulgakov and a figure in Moscow’s literary and theatrical circles in the early 20th century.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded64550dc8190ba44120df00ba498 |
completed | April 15, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9dc0fa288190935ddd3ce61f3721 |
completed | May 9, 2026, 2:36 a.m. |
Created at: April 10, 2026, 2:36 a.m.