Triple
T13669686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Igor Larionov |
E327715
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Larionov |
E1050506
|
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: Larionov | Statement: [Igor Larionov, familyName, Larionov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larionov Context triple: [Igor Larionov, familyName, Larionov]
-
A.
Larionov
chosen
Larionov is a person after whom the KLM line is named, likely recognized for notable contributions or significance related to that context.
-
B.
Lukyanov
Lukyanov is a Russian surname borne by various notable figures in politics, science, and the arts.
-
C.
Vasilevsky
Vasilevsky is a Russian surname most prominently associated with Aleksandr Vasilevsky, a leading Soviet military commander and Marshal of the Soviet Union during World War II.
-
D.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
-
E.
Alekseyev
Alekseyev is a Russian surname borne by various notable figures in Russian history, military, and culture.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65832688190aea688fee0a7cbdb |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f78b0f56048190bcbc6581a8cdc0f5 |
completed | May 3, 2026, 5:51 p.m. |
Created at: April 9, 2026, 9:53 p.m.