Triple

T10568862
Position Surface form Disambiguated ID Type / Status
Subject Wasfi al-Tal E249424 entity
Predicate spouse P13 FINISHED
Object Sadia al-Tal
Sadia al-Tal is known primarily as the wife of the late Jordanian Prime Minister Wasfi al-Tal.
E871895 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: Sadia al-Tal | Statement: [Wasfi al-Tal, spouse, Sadia al-Tal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sadia al-Tal
Context triple: [Wasfi al-Tal, spouse, Sadia al-Tal]
  • A. Latifa al-Zayyat
    Latifa al-Zayyat was an influential Egyptian novelist, critic, and feminist intellectual best known for her pioneering role in modern Arabic literature and women’s rights.
  • B. Aisha al-Mashal
    Aisha al-Mashal is known primarily as the wife of senior Hamas political leader Khaled Mashal.
  • C. Zaynab bint Mazun
    Zaynab bint Mazun was an early Muslim woman from the first generation of Islam, known primarily as the mother of Hafsa bint Umar, one of the wives of the Prophet Muhammad.
  • D. Marj al-Saffar
    Marj al-Saffar is a historic plain in southern Syria that served as a key battlefield and strategic corridor between Damascus and the surrounding regions.
  • E. Safa Zaki
    Safa Zaki is a cognitive psychologist and academic leader who became the first woman to serve as president of Bowdoin College.
  • 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: Sadia al-Tal
Triple: [Wasfi al-Tal, spouse, Sadia al-Tal]
Generated description
Sadia al-Tal is known primarily as the wife of the late Jordanian Prime Minister Wasfi al-Tal.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Sadia al-Tal
Target entity description: Sadia al-Tal is known primarily as the wife of the late Jordanian Prime Minister Wasfi al-Tal.
  • A. Latifa al-Zayyat
    Latifa al-Zayyat was an influential Egyptian novelist, critic, and feminist intellectual best known for her pioneering role in modern Arabic literature and women’s rights.
  • B. Aisha al-Mashal
    Aisha al-Mashal is known primarily as the wife of senior Hamas political leader Khaled Mashal.
  • C. Zaynab bint Mazun
    Zaynab bint Mazun was an early Muslim woman from the first generation of Islam, known primarily as the mother of Hafsa bint Umar, one of the wives of the Prophet Muhammad.
  • D. Marj al-Saffar
    Marj al-Saffar is a historic plain in southern Syria that served as a key battlefield and strategic corridor between Damascus and the surrounding regions.
  • E. Safa Zaki
    Safa Zaki is a cognitive psychologist and academic leader who became the first woman to serve as president of Bowdoin College.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ff53c8190ae7c399d49b585f5 completed April 7, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b4c26ec8190910efdf4a236d654 completed April 10, 2026, 7:11 p.m.
NEDg Description generation batch_69d94e2f16788190bec54b250dad09a9 completed April 10, 2026, 7:23 p.m.
NED2 Entity disambiguation (via description) batch_69d9518517608190b5036694b83f5f58 completed April 10, 2026, 7:37 p.m.
Created at: April 6, 2026, 12:37 p.m.