Triple

T22526934
Position Surface form Disambiguated ID Type / Status
Subject الطريق المسدود E556930 entity
Predicate بطولة P148739 FINISHED
Object زوزو ماضي
زوزو ماضي ممثلة مصرية من جيل الرواد في السينما والمسرح عُرفت بأدوارها القوية في أفلام الخمسينيات والستينيات.
 E1542421 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: زوزو ماضي | Statement: [الطريق المسدود, بطولة, زوزو ماضي]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: زوزو ماضي
Context triple: [الطريق المسدود, بطولة, زوزو ماضي]
  • A. Zulema Yoma
    Zulema Yoma is an Argentine public figure best known as the former First Lady of Argentina during the presidency of Carlos Menem.
  • B. Zozo
    Zozo is a diminutive or affectionate nickname commonly used for someone named Zoe.
  • C. Verla De Peiza
    Verla De Peiza is a Barbadian politician and attorney who has served in prominent leadership roles within Barbados’s major political parties.
  • D. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • E. Elza
    Elza is a feminine given name commonly used in Portuguese- and Spanish-speaking countries, often as a variant of Elsa.
  • 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: زوزو ماضي
Triple: [الطريق المسدود, بطولة, زوزو ماضي]
Generated description
زوزو ماضي ممثلة مصرية من جيل الرواد في السينما والمسرح عُرفت بأدوارها القوية في أفلام الخمسينيات والستينيات.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: زوزو ماضي
Target entity description: زوزو ماضي ممثلة مصرية من جيل الرواد في السينما والمسرح عُرفت بأدوارها القوية في أفلام الخمسينيات والستينيات.
  • A. Zulema Yoma
    Zulema Yoma is an Argentine public figure best known as the former First Lady of Argentina during the presidency of Carlos Menem.
  • B. Zozo
    Zozo is a diminutive or affectionate nickname commonly used for someone named Zoe.
  • C. Verla De Peiza
    Verla De Peiza is a Barbadian politician and attorney who has served in prominent leadership roles within Barbados’s major political parties.
  • D. Suzana
    Suzana is the birth name of American actress Sasha Alexander, known for her roles in television series such as NCIS and Rizzoli & Isles.
  • E. Elza
    Elza is a feminine given name commonly used in Portuguese- and Spanish-speaking countries, often as a variant of Elsa.
  • 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.