Triple
T12785037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anatoly Lukyanov |
E305601
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lukyanov |
E305601
|
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: Lukyanov | Statement: [Anatoly Lukyanov, familyName, Lukyanov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lukyanov Context triple: [Anatoly Lukyanov, familyName, Lukyanov]
-
A.
Lukyanov
chosen
Lukyanov is a Russian surname borne by various notable figures in politics, science, and the arts.
-
B.
Shchusev
Shchusev is a Russian surname most notably associated with Alexey Shchusev, a prominent Soviet architect known for designing Lenin's Mausoleum in Moscow.
-
C.
Ignatyev
Ignatyev is a Russian surname borne by various notable figures in politics, military, sports, and the arts.
-
D.
Yuryatin
Yuryatin is a fictional Russian town in Boris Pasternak’s novel "Doctor Zhivago," serving as a key setting in Lara Antipova’s story.
-
E.
Tolbukhin
Tolbukhin is a Russian surname most notably associated with Soviet military commander Fyodor Tolbukhin, a prominent general during World War II.
- 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e5cb3c08190b8e1e22de8b96e17 |
completed | April 10, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ebeab2081908a6e38351613e3ed |
completed | May 2, 2026, 11:54 p.m. |
Created at: April 9, 2026, 5:29 p.m.