Triple
T20029588
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joffe |
E495084
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Ioffe |
—
|
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: Ioffe | Statement: [Joffe, hasVariant, Ioffe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ioffe Context triple: [Joffe, hasVariant, Ioffe]
-
A.
Ioffe
chosen
Ioffe is a Russian surname most notably associated with the influential Soviet physicist Abram Ioffe, a key figure in the development of modern Russian physics.
-
B.
Firsov
Firsov is a Russian surname most notably associated with Anatoli Firsov, a legendary Soviet ice hockey forward.
-
C.
Kurchatov
Kurchatov is a Russian town in Kursk Oblast best known for hosting the Kursk Nuclear Power Plant and related scientific and industrial facilities.
-
D.
Bogolyubovo
Bogolyubovo is a historic rural locality in Vladimir Oblast, Russia, known for its medieval monastery complex and association with Prince Andrey Bogolyubsky.
-
E.
Vyshnegradsky
Vyshnegradsky is a Russian surname most notably associated with Ivan Vyshnegradsky, a prominent 19th-century Russian statesman and Minister of Finance.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662908df081909a6c8ccf0dd90fff |
completed | April 20, 2026, 5:29 p.m. |
Created at: April 11, 2026, 3:36 p.m.