Triple
T18902339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naomi Novik |
E462366
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Novik |
—
|
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: Novik | Statement: [Naomi Novik, familyName, Novik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Novik Context triple: [Naomi Novik, familyName, Novik]
-
A.
Novik
chosen
Novik is a surname most prominently associated with Naomi Novik, the American fantasy author known for works such as the Temeraire series and "Uprooted."
-
B.
Vorontsov
Vorontsov is the surname of a prominent Russian noble family that produced several influential statesmen, diplomats, and military leaders in the Russian Empire.
-
C.
Odoyev
Odoyev is a historic town in Tula Oblast, Russia, known as an old regional center with roots dating back to medieval Rus.
-
D.
Kurskaya
Kurskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, serving as a major transfer hub in the city’s rapid transit network.
-
E.
Malinovsky
Malinovsky is a Russian surname most notably associated with Soviet military commander and Marshal of the Soviet Union Rodion Malinovsky.
- 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c52a4b4c8190b5821996e3c1741d |
completed | April 20, 2026, 6:18 a.m. |
Created at: April 10, 2026, 11:58 a.m.