Triple

T4623125
Position Surface form Disambiguated ID Type / Status
Subject Ninotchka E101032 entity
Predicate starring P1507 FINISHED
Object Sig Ruman E432718 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: Sig Ruman | Statement: [Ninotchka, starring, Sig Ruman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sig Ruman
Context triple: [Ninotchka, starring, Sig Ruman]
  • A. Sig Ruman chosen
    Sig Ruman was a German-American character actor known for his comedic and often blustery roles in classic Hollywood films, including several collaborations with the Marx Brothers and directors like Ernst Lubitsch.
  • B. Freeman Meskimen
    Freeman Meskimen was an American actor and the husband of actress Marion Ross.
  • C. Warren Jabali
    Warren Jabali was an American professional basketball guard/forward best known for his standout play and All-Star success in the American Basketball Association (ABA) during the late 1960s and early 1970s.
  • D. Bullet Rogan
    Bullet Rogan was a legendary two-way star of Negro league baseball, renowned as both a dominant pitcher and powerful hitter in the early 20th century.
  • E. Alexander Gann
    Alexander Gann is a molecular biologist and science editor known for his work on genetics and for co-authoring influential textbooks in molecular biology.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a053d38819097b3ecbc06aa6e4d completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaa069388190b6482315708b85c2 completed March 21, 2026, 1:55 a.m.
Created at: March 20, 2026, 1:12 p.m.