Triple

T16057344
Position Surface form Disambiguated ID Type / Status
Subject Saadi dynasty E389517 entity
Predicate notableRuler P22 FINISHED
Object Zidan Abu Maali E1111631 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: Zidan Abu Maali | Statement: [Saadi dynasty, notableRuler, Zidan Abu Maali]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zidan Abu Maali
Context triple: [Saadi dynasty, notableRuler, Zidan Abu Maali]
  • A. Zidan Abu Maali chosen
    Zidan Abu Maali was a Saadian sultan of Morocco in the early 17th century, known for his struggles to maintain dynastic power amid internal conflicts and foreign pressures.
  • B. Marwan al-Himar
    Marwan al-Himar, better known as Marwan II, was the last Umayyad caliph who ruled from 744 to 750 CE before the dynasty was overthrown by the Abbasid Revolution.
  • C. Ghaith Abdul-Ahad
    Ghaith Abdul-Ahad is an Iraqi journalist and war correspondent renowned for his frontline reporting from conflict zones across the Middle East.
  • D. Mohammed Amer
    Mohammed Amer is a Palestinian-American stand-up comedian and actor best known for his role on the TV series "Ramy" and his Netflix comedy specials.
  • E. Marwan Kenzari
    Marwan Kenzari is a Dutch-Tunisian actor known for his roles in international films such as Disney’s live-action Aladdin and various Hollywood thrillers and dramas.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837579488190964ca004c2eb01c4 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe678fc8190b36737a9cd29691c completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.