Triple

T22527203
Position Surface form Disambiguated ID Type / Status
Subject هنري بركات E556937 entity
Predicate تعاون_مع P38701 FINISHED
Object ماجدة
ماجدة هي ممثلة مصرية شهيرة من نجمات العصر الذهبي للسينما العربية، عُرفت بأدوارها الرومانسية والاجتماعية وبإنتاجها السينمائي.
 E1542445 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: ماجدة | Statement: [هنري بركات, تعاون_مع, ماجدة]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ماجدة
Context triple: [هنري بركات, تعاون_مع, ماجدة]
  • A. Maysa Hassan
    Maysa Hassan is a fictional character portrayed by Palestinian actress and director Hiam Abbass.
  • B. Kalthoum
    Kalthoum is a jazz album by trumpeter Ibrahim Maalouf that pays tribute to the legendary Egyptian singer Oum Kalthoum.
  • C. Marian Zazeela
    Marian Zazeela is an American visual artist, designer, and musician best known for her pioneering light installations and long-term collaboration with minimalist composer La Monte Young.
  • D. Hoda Baraka
    Hoda Baraka is an Egyptian communications and digital advocacy professional known for her work with international human rights and environmental organizations.
  • E. Ruqaia Hasan
    Ruqaia Hasan was a prominent linguist known for her work in systemic functional linguistics, discourse analysis, and the social semiotic study of language.
  • 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: ماجدة
Triple: [هنري بركات, تعاون_مع, ماجدة]
Generated description
ماجدة هي ممثلة مصرية شهيرة من نجمات العصر الذهبي للسينما العربية، عُرفت بأدوارها الرومانسية والاجتماعية وبإنتاجها السينمائي.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ماجدة
Target entity description: ماجدة هي ممثلة مصرية شهيرة من نجمات العصر الذهبي للسينما العربية، عُرفت بأدوارها الرومانسية والاجتماعية وبإنتاجها السينمائي.
  • A. Maysa Hassan
    Maysa Hassan is a fictional character portrayed by Palestinian actress and director Hiam Abbass.
  • B. Kalthoum
    Kalthoum is a jazz album by trumpeter Ibrahim Maalouf that pays tribute to the legendary Egyptian singer Oum Kalthoum.
  • C. Marian Zazeela
    Marian Zazeela is an American visual artist, designer, and musician best known for her pioneering light installations and long-term collaboration with minimalist composer La Monte Young.
  • D. Hoda Baraka
    Hoda Baraka is an Egyptian communications and digital advocacy professional known for her work with international human rights and environmental organizations.
  • E. Ruqaia Hasan
    Ruqaia Hasan was a prominent linguist known for her work in systemic functional linguistics, discourse analysis, and the social semiotic study of language.
  • 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_6a0b1dd894048190a50e4b3d24d26905 completed May 18, 2026, 2:10 p.m.
NEDg Description generation batch_6a0b2560f8b08190aaba573e06d38d55 completed May 18, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_6a0b2729328481908faf3f88acfc9de1 completed May 18, 2026, 2:50 p.m.
Created at: April 16, 2026, 8:51 p.m.