Triple

T22527079
Position Surface form Disambiguated ID Type / Status
Subject يوم مر ويوم حلو E556934 entity
Predicate hasCastMember P2308 FINISHED
Object جميلة عوض
جميلة عوض هي ممثلة مصرية شابة اشتهرت بتقديم أدوار درامية في السينما والتلفزيون المصري.
 E1545393 NE FINISHED

How this triple was built (4 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: جميلة عوض | Statement: [يوم مر ويوم حلو, hasCastMember, جميلة عوض]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: جميلة عوض
Context triple: [يوم مر ويوم حلو, hasCastMember, جميلة عوض]
  • A. Hani Nassar
    Hani Nassar is an individual notable enough to be specifically cited as a bearer of the surname Nassar.
  • B. مريم فخر الدين
    مريم فخر الدين هي ممثلة مصرية شهيرة من جيل الخمسينيات والستينيات عُرفت بجمالها الأوروبي وأدوارها الرومانسية في السينما العربية.
  • C. Sherine Khalil
    Sherine Khalil is a person whose given name is associated with the entity Athena.
  • D. Shereen Reda
    Shereen Reda is an Egyptian actress and public figure known for her roles in film and television as well as her high-profile presence in Arab media.
  • E. Soheir El Bably
    Soheir El Bably was a celebrated Egyptian actress renowned for her comedic and dramatic roles on stage, television, and in film, making her one of the most beloved figures in modern Egyptian entertainment.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: جميلة عوض
Triple: [يوم مر ويوم حلو, hasCastMember, جميلة عوض]
Generated description
جميلة عوض هي ممثلة مصرية شابة اشتهرت بتقديم أدوار درامية في السينما والتلفزيون المصري.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: جميلة عوض
Target entity description: جميلة عوض هي ممثلة مصرية شابة اشتهرت بتقديم أدوار درامية في السينما والتلفزيون المصري.
  • A. Hani Nassar
    Hani Nassar is an individual notable enough to be specifically cited as a bearer of the surname Nassar.
  • B. مريم فخر الدين
    مريم فخر الدين هي ممثلة مصرية شهيرة من جيل الخمسينيات والستينيات عُرفت بجمالها الأوروبي وأدوارها الرومانسية في السينما العربية.
  • C. Sherine Khalil
    Sherine Khalil is a person whose given name is associated with the entity Athena.
  • D. Shereen Reda
    Shereen Reda is an Egyptian actress and public figure known for her roles in film and television as well as her high-profile presence in Arab media.
  • E. Soheir El Bably
    Soheir El Bably was a celebrated Egyptian actress renowned for her comedic and dramatic roles on stage, television, and in film, making her one of the most beloved figures in modern Egyptian entertainment.
  • F. None of above. chosen

Provenance (5 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_69e11e57483c8190b0887c4f8ff26446 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ed411488190a51320930b9805c2 completed April 29, 2026, 1:28 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b4debca3c8190b32c37e6c2c2ff0a completed May 18, 2026, 5:35 p.m.
NEDg Description generation batch_6a0b4f353960819088a3960753a2751c completed May 18, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_6a0b4f96e8388190bb054d4b921b2a59 completed May 18, 2026, 5:42 p.m.
Created at: April 16, 2026, 8:51 p.m.