Triple
T1686443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mikhail |
E36451
|
entity |
| Predicate | script |
P505
|
FINISHED |
| Object | Михаил |
E36451
|
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: Михаил | Statement: [Mikhail, script, Михаил]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Михаил Context triple: [Mikhail, script, Михаил]
-
A.
Mikhail
chosen
Mikhail is a common Russian male given name, famously borne by Soviet leader Mikhail Gorbachev.
-
B.
Aleksandr
Aleksandr is a common Russian male given name of Greek origin, equivalent to Alexander in English.
-
C.
Vasily
Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
D.
Nikolay
Nikolay is a masculine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Nicholas in English.
-
E.
Vsevolod
Vsevolod is a masculine given name of Slavic origin, most notably borne by the influential Russian theatre director Vsevolod Meyerhold.
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6293c368819094ab0f615e418647 |
completed | March 6, 2026, 5:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b030e23ea081909737f5fd2d3c8dfb |
completed | March 10, 2026, 2:55 p.m. |
Created at: March 4, 2026, 7:29 p.m.