Triple

T15390795
Position Surface form Disambiguated ID Type / Status
Subject Amy Dubanowski E368037 entity
Predicate relative P37 FINISHED
Object Adam Dubanowski E1208945 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: Adam Dubanowski | Statement: [Amy Dubanowski, relative, Adam Dubanowski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adam Dubanowski
Context triple: [Amy Dubanowski, relative, Adam Dubanowski]
  • A. Adam Dubanowski chosen
    Adam Dubanowski is a character in the TV series "Unbreakable Kimmy Schmidt," known primarily as the husband of Amy Dubanowski.
  • B. Dauber Dybinski
    Dauber Dybinski is a dim-witted but good-hearted assistant coach character from the American sitcom "Coach."
  • C. Adam Bielecki
    Adam Bielecki is a Polish high-altitude mountaineer renowned for pioneering bold winter ascents in the Himalayas and Karakoram.
  • D. Eric Dapkewicz
    Eric Dapkewicz is a film editor best known for his work on major animated features, including DreamWorks Animation’s "Puss in Boots."
  • E. Daniel Dubiecki
    Daniel Dubiecki is an American film producer known for his work on acclaimed movies such as "Up in the Air" and other high-profile Hollywood projects.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e7727a081908eff45bbc1633c8a completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0035450810819092796c556dfa8ed3 completed May 10, 2026, 7:35 a.m.
Created at: April 10, 2026, 3:19 a.m.