Triple

T3290044
Position Surface form Disambiguated ID Type / Status
Subject Salma Hayek E69078 entity
Predicate givenName P17 FINISHED
Object Salma
Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
 E343693 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: Salma | Statement: [Salma Hayek, givenName, Salma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Salma
Context triple: [Salma Hayek, givenName, Salma]
  • A. Shabana
    Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
  • B. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • C. Riza Aziz
    Riza Aziz is a Malaysian film producer and co-founder of Red Granite Pictures, known for financing high-profile Hollywood films and being embroiled in the 1MDB corruption scandal.
  • D. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • E. Habiba
    Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
  • 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: Salma
Triple: [Salma Hayek, givenName, Salma]
Generated description
Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Salma
Target entity description: Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
  • A. Shabana
    Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
  • B. Zohra
    Zohra is a character in Naguib Mahfouz’s novel "Miramar," which centers on the lives and conflicts of residents in a pension in Alexandria, Egypt.
  • C. Riza Aziz
    Riza Aziz is a Malaysian film producer and co-founder of Red Granite Pictures, known for financing high-profile Hollywood films and being embroiled in the 1MDB corruption scandal.
  • D. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • E. Habiba
    Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb05bd6b08190bcb9f0e5da82bc21 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e862835881909c2f3b8f86f10742 completed March 12, 2026, 4:22 p.m.
NEDg Description generation batch_69b2e8f6a7c48190bc457f348c3a7179 completed March 12, 2026, 4:25 p.m.
NED2 Entity disambiguation (via description) batch_69b2e986dcc88190bd3daa6c6fdcb50e completed March 12, 2026, 4:27 p.m.
Created at: March 8, 2026, 3:10 p.m.