Triple

T20389967
Position Surface form Disambiguated ID Type / Status
Subject Dead Man E498058 entity
Predicate starring P1507 FINISHED
Object Mili Avital 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: Mili Avital | Statement: [Dead Man, starring, Mili Avital]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mili Avital
Context triple: [Dead Man, starring, Mili Avital]
  • A. Mili Avital chosen
    Mili Avital is an Israeli-American actress known for her roles in film and television, including a prominent part in the science fiction movie "Stargate."
  • B. Nili Priel
    Nili Priel is an Israeli public figure best known as the wife of former Prime Minister and Defense Minister Ehud Barak.
  • C. Karmei Tzur
    Karmei Tzur is an Israeli settlement in the Gush Etzion region of the West Bank, located north of Hebron and known as a small religious community.
  • D. Daliah Lavi
    Daliah Lavi was an Israeli actress, singer, and model best known internationally for her roles in 1960s European and Hollywood films, particularly in stylish spy spoofs and adventure movies.
  • E. Tamar Shalev
    Tamar Shalev is known as the wife of the late Israeli author and columnist Meir Shalev.
  • 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_69e0b4a71ebc8190b153a36c738730f4 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6790e65a081909832855758fffd14 completed April 20, 2026, 7:05 p.m.
Created at: April 16, 2026, 11:28 a.m.