Triple

T17152726
Position Surface form Disambiguated ID Type / Status
Subject Ali Laarayedh E416261 entity
Predicate succeededBy P78 FINISHED
Object Mehdi Jomaa 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: Mehdi Jomaa | Statement: [Ali Laarayedh, succeededBy, Mehdi Jomaa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mehdi Jomaa
Context triple: [Ali Laarayedh, succeededBy, Mehdi Jomaa]
  • A. Mehdi Jomaa chosen
    Mehdi Jomaa is a Tunisian engineer and politician who served as Tunisia’s interim prime minister during the country’s post-revolution transitional period.
  • B. Ahmed Hachani
    Ahmed Hachani is a Tunisian politician who has served as head of government under President Kais Saied.
  • C. Franck Khalfoun
    Franck Khalfoun is a French-American filmmaker and actor best known for directing horror and thriller films such as the 2012 remake of "Maniac."
  • D. 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.
  • E. Tarak Ben Ammar
    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.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f40861e08190bad1a3ec87691132 completed April 18, 2026, 9:13 p.m.
Created at: April 10, 2026, 5:36 a.m.