Triple

T8938646
Position Surface form Disambiguated ID Type / Status
Subject Samira Ibrahim E212840 entity
Predicate givenName P17 FINISHED
Object Samira
Samira is a feminine given name of Arabic origin commonly used across the Middle East, North Africa, and South Asia.
 E767316 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: Samira | Statement: [Samira Ibrahim, givenName, Samira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Samira
Context triple: [Samira Ibrahim, givenName, Samira]
  • A. Salma
    Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
  • B. Ayesha
    Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
  • C. Zoya
    Zoya is a feminine given name of Russian origin, widely recognized through its association with Soviet World War II partisan Zoya Kosmodemyanskaya.
  • D. Najma
    Najma was the mother of Ali al-Rida, the eighth Shia Imam, and is venerated in Islamic tradition for her piety and role in his upbringing.
  • E. Karima
    Karima is a town in northern Sudan known as a gateway to the ancient Nubian archaeological area around Gebel Barkal and the Napatan sites.
  • 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: Samira
Triple: [Samira Ibrahim, givenName, Samira]
Generated description
Samira is a feminine given name of Arabic origin commonly used across the Middle East, North Africa, and South Asia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Samira
Target entity description: Samira is a feminine given name of Arabic origin commonly used across the Middle East, North Africa, and South Asia.
  • A. Salma
    Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
  • B. Ayesha
    Ayesha is a central fictional heroine in Bankim Chandra Chattopadhyay’s historical Bengali novel "Durgeshnandini," known for her beauty, courage, and tragic love.
  • C. Zoya
    Zoya is a feminine given name of Russian origin, widely recognized through its association with Soviet World War II partisan Zoya Kosmodemyanskaya.
  • D. Najma
    Najma was the mother of Ali al-Rida, the eighth Shia Imam, and is venerated in Islamic tradition for her piety and role in his upbringing.
  • E. Karima
    Karima is a town in northern Sudan known as a gateway to the ancient Nubian archaeological area around Gebel Barkal and the Napatan sites.
  • 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_69ca839694c88190b324ffeb43d23b08 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66b57a348190979effe4f9998eb7 completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1eb308c81909f5be133c75ad568 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc24b4fe481909b7c4f58b787a21e completed April 3, 2026, 1:36 p.m.
NED2 Entity disambiguation (via description) batch_69cfc33fbedc8190a8f04ec6f43891f0 completed April 3, 2026, 1:40 p.m.
Created at: March 30, 2026, 6:58 p.m.