Triple

T17263045
Position Surface form Disambiguated ID Type / Status
Subject Wassila Ben Ammar E419053 entity
Predicate familyName P18 FINISHED
Object Ben Ammar 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: Ben Ammar | Statement: [Wassila Ben Ammar, familyName, Ben Ammar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ben Ammar
Context triple: [Wassila Ben Ammar, familyName, Ben Ammar]
  • A. Tarak Ben Ammar chosen
    Tarak Ben Ammar is a Tunisian-French film producer and media mogul known for financing and producing numerous international films and working closely with major Hollywood studios and European cinema.
  • B. Mehdi Jomaa
    Mehdi Jomaa is a Tunisian engineer and politician who served as Tunisia’s interim prime minister during the country’s post-revolution transitional period.
  • C. Ahmed Ounaies
    Ahmed Ounaies is a Tunisian politician and diplomat who briefly served as Tunisia’s Minister of Foreign Affairs following the 2011 revolution.
  • D. Youssef Amrani
    Youssef Amrani is a Moroccan diplomat who has held several high-level positions in regional and international organizations, particularly focused on Euro-Mediterranean cooperation.
  • E. Issam Zahreddine
    Issam Zahreddine was a prominent Syrian Republican Guard general best known for leading government forces in some of the fiercest battles of the Syrian Civil War.
  • 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_69d886d9ab108190b70edd8d17aa1204 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42f4379848190add32ba8e5f93527 completed April 19, 2026, 1:26 a.m.
Created at: April 10, 2026, 5:40 a.m.