Triple

T6505716
Position Surface form Disambiguated ID Type / Status
Subject ميرامار E150000 entity
Predicate الشخصية_الرئيسية P39597 FINISHED
Object حسني علام E164491 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: حسني علام | Statement: [ميرامار, الشخصية_الرئيسية, حسني علام]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: حسني علام
Context triple: [ميرامار, الشخصية_الرئيسية, حسني علام]
  • A. Hosny Allam chosen
    Hosny Allam is a fictional character from Naguib Mahfouz’s novel "Miramar," representing one of the diverse boarders at the Alexandria pension whose intersecting lives drive the story’s social and political themes.
  • B. فتحي سرور
    فتحي سرور هو سياسي مصري بارز شغل منصب رئيس مجلس الشعب لسنوات طويلة وكان من أبرز رموز النظام قبل ثورة 25 يناير.
  • C. Hussein Kamel
    Hussein Kamel was the Sultan of Egypt from 1914 to 1917, installed by the British during World War I after they deposed Khedive Abbas II and declared Egypt a protectorate.
  • D. Ahmed Fakhry
    Ahmed Fakhry was a prominent Egyptian archaeologist and Egyptologist known for his extensive excavations and research on Old Kingdom pyramids and desert monuments.
  • E. Abdallah Gheith
    Abdallah Gheith was a prominent Egyptian actor known for his powerful performances in film, television, and theater during the late 20th century.
  • 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_69c687ef291081909d437f035eef1cda completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ad92c624819086dbb12b4f6b78d3 completed March 27, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d50b15f081909bb7024fa57d528b completed March 27, 2026, 7:05 p.m.
Created at: March 27, 2026, 1:43 p.m.