Triple

T23061846
Position Surface form Disambiguated ID Type / Status
Subject Pour elle E574922 entity
Predicate starring P1507 FINISHED
Object Moussa Maaskri 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: Moussa Maaskri | Statement: [Pour elle, starring, Moussa Maaskri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moussa Maaskri
Context triple: [Pour elle, starring, Moussa Maaskri]
  • A. Moussa Maaskri chosen
    Moussa Maaskri is a French actor known for his supporting roles in crime dramas and action films, often portraying tough or morally ambiguous characters.
  • B. Ahmed Mestiri
    Ahmed Mestiri was a prominent Tunisian politician and lawyer known for his opposition to authoritarian rule and his role in the country’s post-independence political life.
  • C. Hamadi Jebali
    Hamadi Jebali is a Tunisian politician and former prime minister who played a key role in the country’s post-Arab Spring transitional government.
  • D. Ahmed Ounaies
    Ahmed Ounaies is a Tunisian politician and diplomat who briefly served as Tunisia’s Minister of Foreign Affairs following the 2011 revolution.
  • E. Ahmed Hachani
    Ahmed Hachani is a Tunisian politician who has served as head of government under President Kais Saied.
  • 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_69e245bd6e4c8190bb8942245b68cad5 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899ff96081908d89a07a3b1065c8 completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.