Triple
T13410206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikita Mazepin |
E320065
|
entity |
| Predicate | hasTwitterUsername |
P2943
|
FINISHED |
| Object | nikita_mazepin |
E1039929
|
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: nikita_mazepin | Statement: [Nikita Mazepin, hasTwitterUsername, nikita_mazepin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: nikita_mazepin Context triple: [Nikita Mazepin, hasTwitterUsername, nikita_mazepin]
-
A.
nikita_mazepin
chosen
nikita_mazepin is the Instagram handle of Russian racing driver Nikita Mazepin, known for his stint in Formula One with the Haas F1 Team.
-
B.
Nikitin
Nikitin is a Russian surname borne by numerous notable figures in fields such as art, science, and sports.
-
C.
Nikolay
Nikolay is a masculine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Nicholas in English.
-
D.
Nik
Nik is one of the three futuristic, anime-style "Spheriks" characters that served as official mascots for the 2002 FIFA World Cup in South Korea and Japan.
-
E.
Nikita Anisimov
Nikita Anisimov is a Russian academic and university administrator who serves as the rector of the National Research University Higher School of Economics (HSE) in Moscow.
- 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb3facc819088c1af3b59237e7a |
completed | April 12, 2026, 2:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739857dd4819087e64b956a814939 |
completed | May 3, 2026, 12:03 p.m. |
Created at: April 9, 2026, 9:35 p.m.