Triple
T14494447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Feodor Alexandrovich of Russia |
E359454
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Feodor |
E236337
|
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: Feodor | Statement: [Prince Feodor Alexandrovich of Russia, givenName, Feodor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Feodor Context triple: [Prince Feodor Alexandrovich of Russia, givenName, Feodor]
-
A.
Fyodor
chosen
Fyodor is a masculine given name of Russian origin, most famously borne by the novelist Fyodor Dostoevsky.
-
B.
Vasily
Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
C.
Rodion
Rodion is a masculine given name of Slavic origin, most notably borne by Soviet military commander Rodion Malinovsky.
-
D.
Innokenty
Innokenty is a masculine given name of Slavic origin, most notably borne by the renowned Russian actor Innokenty Smoktunovsky.
-
E.
Foma Gordeyev
Foma Gordeyev is a novel by Russian writer Maksim Gorky that portrays the moral and spiritual decline of a wealthy merchant’s son amid the social tensions of late 19th-century Russia.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de930f34d08190b4b30e54e2f702ed |
completed | April 14, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bbfc6048190897f064a5686ebf8 |
completed | May 9, 2026, 1:19 a.m. |
Created at: April 10, 2026, 1:21 a.m.