Triple
T13599915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Onika Tanya Maraj |
E324915
|
entity |
| Predicate | hasAlterEgo |
P39
|
FINISHED |
| Object | Roman Zolanski |
E344730
|
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: Roman Zolanski | Statement: [Onika Tanya Maraj, hasAlterEgo, Roman Zolanski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roman Zolanski Context triple: [Onika Tanya Maraj, hasAlterEgo, Roman Zolanski]
-
A.
Roman Zolanski
chosen
Roman Zolanski is one of Nicki Minaj’s most famous and flamboyant alter egos, characterized by his wild, aggressive, and theatrical persona in her music and performances.
-
B.
Marek Zaleski
Marek Zaleski is a Polish literary critic and essayist known for his work on modern Polish literature and literary theory.
-
C.
Daniel Olbrychski
Daniel Olbrychski is a renowned Polish film and theatre actor known for his roles in classic Polish cinema and international productions.
-
D.
Jan Zaleski
Jan Zaleski was a Polish biochemist known for his pioneering research in organic and physiological chemistry in the early 20th century.
-
E.
Stefan Czapsky
Stefan Czapsky is an American cinematographer best known for his visually distinctive work on films such as Tim Burton’s "Edward Scissorhands" and "Batman Returns."
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0795acc8190a08667ab9dcb0d44 |
completed | April 12, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bcc1ed88190bbf6c83001703b84 |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.