Triple

T22982198
Position Surface form Disambiguated ID Type / Status
Subject Henry Barakat E571497 entity
Predicate notableWork P4 FINISHED
Object Hassan wa Naeima 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: Hassan wa Naeima | Statement: [Henry Barakat, notableWork, Hassan wa Naeima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hassan wa Naeima
Context triple: [Henry Barakat, notableWork, Hassan wa Naeima]
  • A. Hassan wa Naima chosen
    Hassan wa Naima is a classic Egyptian romantic drama film, often likened to "Romeo and Juliet," directed by Henry Barakat and based on a famous Egyptian folk love story.
  • B. Habiba
    Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
  • C. Asmaa
    Asmaa is a feminine given name of Arabic origin commonly used in many Muslim-majority countries.
  • D. Bani Na'im
    Bani Na'im is a Palestinian town located southeast of Hebron in the southern West Bank, known for its agricultural character and historical significance.
  • E. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • 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_69e245b3c50481908bb3741ec9f40862 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1829645f88190aea1b96ea595ff60 completed April 29, 2026, 4:01 a.m.
Created at: April 17, 2026, 3:49 p.m.