Triple
T21018184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niki Karimi |
E517734
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Niki Karimi |
E517734
|
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: Niki Karimi | Statement: [Niki Karimi, name, Niki Karimi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Niki Karimi Context triple: [Niki Karimi, name, Niki Karimi]
-
A.
Niki Karimi
chosen
Niki Karimi is a prominent Iranian actress, director, and screenwriter known for her influential role in contemporary Iranian cinema and her award-winning performances and films.
-
B.
Nima Khandan
Nima Khandan is the son of prominent Iranian human rights lawyer and activist Nasrin Sotoudeh.
-
C.
Sia Alipour
Sia Alipour is an actor known for his role in the Iranian television series "Tehran."
-
D.
Soraya Taheri
Soraya Taheri is a key character in Khaled Hosseini’s novel "The Kite Runner," known as Amir’s supportive and resilient wife who helps him confront his past.
-
E.
Sarah Solemani
Sarah Solemani is a British actress and writer known for her roles in television comedies like "Him & Her" and "Bad Education" as well as various film and stage performances.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5a27f08190b26828a6a7b59f7c |
completed | April 21, 2026, 4:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a098fe1d28c8190802140e3ee44716d |
completed | May 17, 2026, 9:52 a.m. |
Created at: April 16, 2026, 1:54 p.m.