Triple

T4867631
Position Surface form Disambiguated ID Type / Status
Subject Cohen E109009 entity
Predicate scriptVariant P4680 FINISHED
Object Kahane E412932 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: Kahane | Statement: [Cohen, scriptVariant, Kahane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kahane
Context triple: [Cohen, scriptVariant, Kahane]
  • A. Nathan Kahane
    Nathan Kahane is a film producer and studio executive known for backing numerous successful Hollywood comedies and genre films.
  • B. 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.
  • C. Israel Beilin
    Israel Beilin, better known as Irving Berlin, was a Russian-born American composer and lyricist who became one of the most prolific and influential songwriters in the history of popular music.
  • D. Mordechai Namir
    Mordechai Namir was an Israeli politician, trade union leader, and longtime mayor of Tel Aviv who played a prominent role in the country’s early labor movement and governance.
  • E. Jean-Pierre Kahane chosen
    Jean-Pierre Kahane was a French mathematician known for his influential work in harmonic analysis, probability theory, and the geometry of Banach spaces.
  • 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_69bd440d96a48190b0c87069adef2af1 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6d7bb0b88190bbc24498619910fc completed March 20, 2026, 3:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69be67e5d96c8190b2a509d9fb81211a completed March 21, 2026, 9:41 a.m.
Created at: March 20, 2026, 1:26 p.m.