Triple

T5676527
Position Surface form Disambiguated ID Type / Status
Subject How to Make It in America E125098 entity
Predicate starring P1507 FINISHED
Object Victor Rasuk E224899 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: Victor Rasuk | Statement: [How to Make It in America, starring, Victor Rasuk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor Rasuk
Context triple: [How to Make It in America, starring, Victor Rasuk]
  • A. Victor Rasuk chosen
    Victor Rasuk is an American actor known for roles in films like "Lords of Dogtown" and "How to Make It in America," as well as supporting parts in major franchises.
  • B. Victor Grinich
    Victor Grinich was an American electrical engineer and entrepreneur best known as one of the Traitorous Eight who co-founded Fairchild Semiconductor, helping launch Silicon Valley’s semiconductor industry.
  • C. Vladimir Sherwood
    Vladimir Sherwood was a Russian architect best known for his Neo-Russian style designs in Moscow during the late 19th century.
  • D. Victor John Raschi
    Victor John Raschi was an American Major League Baseball right-handed pitcher best known for his dominant years with the New York Yankees in the late 1940s and early 1950s.
  • E. Alec Miloslavsky
    Alec Miloslavsky is a technology entrepreneur best known as a co-founder of the customer experience and contact center software company Genesys.
  • 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_69c008295c808190acfe78915e7d656a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c023728f488190a3622844d78caa13 completed March 22, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07dc5d8b08190b4646853f68beb62 completed March 22, 2026, 11:39 p.m.
Created at: March 22, 2026, 3:43 p.m.