Triple

T19850602
Position Surface form Disambiguated ID Type / Status
Subject Kahen E476981 entity
Predicate hasVariantSpelling P457 FINISHED
Object Kahane NE NERFINISHED

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: Kahane | Statement: [Kahen, hasVariantSpelling, Kahane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kahane
Context triple: [Kahen, hasVariantSpelling, Kahane]
  • A. Kahane chosen
    Kahane is a surname and variant of "Kagan" commonly associated with Jewish families and notable figures in religious, political, and cultural spheres.
  • B. Avigdor Kahalani
    Avigdor Kahalani is an Israeli politician and highly decorated former Israel Defense Forces officer, renowned for his leadership in the Yom Kippur War and later service in various ministerial roles.
  • C. Nathan Kahane
    Nathan Kahane is a film producer and studio executive known for backing numerous successful Hollywood comedies and genre films.
  • D. Yitzhak Kahan
    Yitzhak Kahan was an Israeli jurist who served as President of the Supreme Court of Israel and chaired the commission that investigated the Sabra and Shatila massacre.
  • E. Ehud Shabtai
    Ehud Shabtai is an Israeli software engineer and entrepreneur best known as the co-founder and chief architect of the GPS-based navigation app Waze.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51d39d081909bcfafeaaf3d2fcc completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e65867b5408190bbd12ca567c4705f completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.