Triple
T14430764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Chernus |
E357820
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Chernus
Chernus is a surname most notably associated with American actor Michael Chernus, known for his work in film, television, and theater.
|
E1098762
|
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: Chernus | Statement: [Michael Chernus, familyName, Chernus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chernus Context triple: [Michael Chernus, familyName, Chernus]
-
A.
Evilenko
Evilenko is a 2004 psychological horror-thriller film loosely inspired by the crimes of Soviet serial killer Andrei Chikatilo.
-
B.
Zahar Berkut
"Zahar Berkut" is a historical novella by Ukrainian writer Ivan Franko that depicts the struggle of a Carpathian mountain community against Mongol invaders in the 13th century.
-
C.
Nozdryov
Nozdryov is a boisterous, dishonest, and troublemaking landowner in Nikolai Gogol's novel "Dead Souls," known for his compulsive lying and love of gambling and chaos.
-
D.
Lyova
Lyova is a Russian diminutive form of the male given name Lev.
-
E.
Chernomor
Chernomor is a villainous sorcerer with a long magical beard who abducts the heroine in Alexander Pushkin’s narrative poem "Ruslan and Ludmila."
- 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: Chernus Triple: [Michael Chernus, familyName, Chernus]
Generated description
Chernus is a surname most notably associated with American actor Michael Chernus, known for his work in film, television, and theater.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chernus Target entity description: Chernus is a surname most notably associated with American actor Michael Chernus, known for his work in film, television, and theater.
-
A.
Evilenko
Evilenko is a 2004 psychological horror-thriller film loosely inspired by the crimes of Soviet serial killer Andrei Chikatilo.
-
B.
Zahar Berkut
"Zahar Berkut" is a historical novella by Ukrainian writer Ivan Franko that depicts the struggle of a Carpathian mountain community against Mongol invaders in the 13th century.
-
C.
Nozdryov
Nozdryov is a boisterous, dishonest, and troublemaking landowner in Nikolai Gogol's novel "Dead Souls," known for his compulsive lying and love of gambling and chaos.
-
D.
Lyova
Lyova is a Russian diminutive form of the male given name Lev.
-
E.
Chernomor
Chernomor is a villainous sorcerer with a long magical beard who abducts the heroine in Alexander Pushkin’s narrative poem "Ruslan and Ludmila."
- 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_69d8279402a88190821ffa39ae15bccf |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de914570f08190b1c7c1c57a0cb476 |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bd3e6c48190b4fc3794202a0c3f |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5de2ebac81908042f6696400a74d |
completed | May 8, 2026, 3:52 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5e6927c88190add8d31989bec043 |
completed | May 8, 2026, 3:54 a.m. |
Created at: April 10, 2026, 1:18 a.m.