Triple
T22103882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bad Education (2019 film) |
E546236
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object |
Edward Vaisman
Edward Vaisman is a film producer best known for his work on the 2019 dark comedy-drama "Bad Education."
|
E1521658
|
NE FINISHED |
How this triple was built (4 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: Edward Vaisman | Statement: [Bad Education (2019 film), producer, Edward Vaisman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward Vaisman Context triple: [Bad Education (2019 film), producer, Edward Vaisman]
-
A.
Igor Youskevitch
Igor Youskevitch was a renowned 20th-century ballet dancer celebrated for his powerful technique and leading roles with Ballet Theatre (now American Ballet Theatre).
-
B.
Yuri Levitansky
Yuri Levitansky was a prominent Soviet and Russian poet known for his introspective, philosophical verse and his nuanced reflections on war and the human condition.
-
C.
Vladimir Gelfreikh
Vladimir Gelfreikh was a Soviet architect known for his prominent Stalinist-era designs and contributions to major state buildings in Moscow.
-
D.
Roman Varshavsky
Roman Varshavsky is a voice actor best known for portraying the Call of Duty antagonist Vladimir Makarov.
-
E.
Valentin Kamensky
Valentin Kamensky was a Soviet architect best known for co-designing major war memorials, including the Monument to the Heroic Defenders of Leningrad in Saint Petersburg.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Edward Vaisman Triple: [Bad Education (2019 film), producer, Edward Vaisman]
Generated description
Edward Vaisman is a film producer best known for his work on the 2019 dark comedy-drama "Bad Education."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Edward Vaisman Target entity description: Edward Vaisman is a film producer best known for his work on the 2019 dark comedy-drama "Bad Education."
-
A.
Igor Youskevitch
Igor Youskevitch was a renowned 20th-century ballet dancer celebrated for his powerful technique and leading roles with Ballet Theatre (now American Ballet Theatre).
-
B.
Yuri Levitansky
Yuri Levitansky was a prominent Soviet and Russian poet known for his introspective, philosophical verse and his nuanced reflections on war and the human condition.
-
C.
Vladimir Gelfreikh
Vladimir Gelfreikh was a Soviet architect known for his prominent Stalinist-era designs and contributions to major state buildings in Moscow.
-
D.
Roman Varshavsky
Roman Varshavsky is a voice actor best known for portraying the Call of Duty antagonist Vladimir Makarov.
-
E.
Valentin Kamensky
Valentin Kamensky was a Soviet architect best known for co-designing major war memorials, including the Monument to the Heroic Defenders of Leningrad in Saint Petersburg.
- F. None of above. chosen
Provenance (5 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1291815f88190a6eaf73e444dc1c2 |
completed | April 28, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a96ed8b508190b92bcf06d2f69b25 |
completed | May 18, 2026, 4:34 a.m. |
| NEDg | Description generation | batch_6a0a97a03abc8190a0158fe2ad6c14d7 |
completed | May 18, 2026, 4:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a981c96648190b295c1667f1c3648 |
completed | May 18, 2026, 4:39 a.m. |
Created at: April 16, 2026, 8:30 p.m.