Triple
T15795364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ნიკო ფიროსმანი |
E382963
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | ნიკო ფიროსმანი |
E382963
|
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: ნიკო ფიროსმანი | Statement: [ნიკო ფიროსმანი, name, ნიკო ფიროსმანი]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ნიკო ფიროსმანი Context triple: [ნიკო ფიროსმანი, name, ნიკო ფიროსმანი]
-
A.
ნიკო ფიროსმანი
chosen
ნიკო ფიროსმანი იყო თვითნასწავლი ქართველი მხატვარი, რომლის ნაივური სტილის ნამუშევრები დღეს ქართული კულტურის ერთ-ერთ ყველაზე ცნობილ და გამორჩეულ სიმბოლოდ ითვლება.
-
B.
Nick Nikas
Nick Nikas is one of the central characters in the crime thriller film "Good Time," portrayed as a desperate and impulsive man entangled in a botched robbery and its chaotic aftermath.
-
C.
Alex Nesic
Alex Nesic is an actor best known for his role in the television drama series "Sleeper Cell."
-
D.
Frank Nitto
Frank Nitto was an American mobster who became a leading figure in Al Capone’s Chicago Outfit during the Prohibition era.
-
E.
Michael Nuccio
Michael Nuccio is an actor known for appearing in the psychological thriller film "In the Cut."
- 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_69d86da16e188190b89af699f1ed0bfe |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4dc887081909d682ae153f06d97 |
completed | April 16, 2026, 10:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90aea81c8190ad8bc0cdedf4b77a |
completed | May 9, 2026, 7:53 p.m. |
Created at: April 10, 2026, 4:48 a.m.