Triple
T3717925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sholom Aleichem |
E81574
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Stempenyu |
E88489
|
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: Stempenyu | Statement: [Sholom Aleichem, notableWork, Stempenyu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stempenyu Context triple: [Sholom Aleichem, notableWork, Stempenyu]
-
A.
Stempenyu
chosen
Stempenyu is a Yiddish novel by Sholem Aleichem that portrays the life and romantic entanglements of a charismatic klezmer violinist in a Jewish shtetl.
-
B.
Anastas
Anastas is a masculine given name most notably borne by Soviet statesman Anastas Mikoyan.
-
C.
Gerasim
Gerasim is the compassionate peasant servant in Leo Tolstoy’s novella "The Death of Ivan Ilyich," known for his honesty, simplicity, and humane care for the dying protagonist.
-
D.
Grigori
Grigori is the given name of Grigori Rasputin, the controversial Russian mystic and advisor to the Romanov royal family in the early 20th century.
-
E.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
- 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adca984844819087a2f6b20d2f19e7 |
completed | March 8, 2026, 7:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4ce1260948190b4707337e9427c2c |
completed | March 14, 2026, 2:55 a.m. |
Created at: March 8, 2026, 3:33 p.m.