Triple
T21622428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slabodka yeshiva |
E533610
|
entity |
| Predicate | hasStudent |
P48
|
FINISHED |
| Object | Reuven Grozovsky |
—
|
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: Reuven Grozovsky | Statement: [Slabodka yeshiva, hasStudent, Reuven Grozovsky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Reuven Grozovsky Context triple: [Slabodka yeshiva, hasStudent, Reuven Grozovsky]
-
A.
Reuven Grozovsky
chosen
Reuven Grozovsky was a prominent 20th-century Lithuanian rabbi and Talmudic scholar, renowned as a leading figure in the yeshiva world and a major authority in Jewish law and ethics.
-
B.
Dovid Kuperman
Dovid Kuperman is a central figure in the novel "Disobedience," whose personal journey explores themes of faith, identity, and rebellion within a strict religious community.
-
C.
Menachem Savidor
Menachem Savidor was an Israeli politician who served as Speaker of the Knesset and was a member of the Likud party.
-
D.
Michael Aronov
Michael Aronov is an American actor known for his work in film, television, and theater, including a role in the historical drama "Operation Finale."
-
E.
Yossi Graber
Yossi Graber was an Israeli actor known for his work in film, television, and theater.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef3bb0c42c8190997fbeb7a764d60e |
completed | April 27, 2026, 10:34 a.m. |
Created at: April 16, 2026, 6:34 p.m.