Triple

T14879506
Position Surface form Disambiguated ID Type / Status
Subject Zelda Rubinstein E349960 entity
Predicate familyName P18 FINISHED
Object Rubinstein E406756 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: Rubinstein | Statement: [Zelda Rubinstein, familyName, Rubinstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rubinstein
Context triple: [Zelda Rubinstein, familyName, Rubinstein]
  • A. Rubinstein chosen
    Rubinstein is a Jewish surname of German and Yiddish origin borne by numerous notable figures in fields such as music, mathematics, and economics.
  • B. Rosenstein
    Rosenstein is a surname most notably associated with Justin Rosenstein, the American software programmer and co-founder of Asana.
  • C. Schoenfeld
    Schoenfeld is a German-origin surname borne by various notable individuals across fields such as music, sports, and academia.
  • D. Rubenfeld
    Rubenfeld is a surname most notably associated with American actor and comedian Paul Reubens, best known for creating and portraying the character Pee-wee Herman.
  • E. Rubin Kazan
    Rubin Kazan is a Russian professional football club based in Kazan, known for competing in the Russian Premier League and winning multiple domestic titles in the late 2000s.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5e622388190b2bf91cd10b9821d completed April 15, 2026, 12:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b5670108190b41ef95dc318be60 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:55 a.m.