Triple

T6299190
Position Surface form Disambiguated ID Type / Status
Subject Sayyida Nafisa E141207 entity
Predicate hasHonorific P2097 FINISHED
Object Sharifa
Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
 E593887 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: Sharifa | Statement: [Sayyida Nafisa, hasHonorific, Sharifa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sharifa
Context triple: [Sayyida Nafisa, hasHonorific, Sharifa]
  • A. Fawzia
    Fawzia is a feminine given name most famously borne by Princess Fawzia of Egypt, a 20th-century Egyptian royal and first wife of Iran’s Shah Mohammad Reza Pahlavi.
  • 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. Habiba
    Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
  • D. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • E. Buraydah
    Buraydah is a major city in central Saudi Arabia and the capital of Al-Qassim Region, known as an important agricultural and commercial center.
  • 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: Sharifa
Triple: [Sayyida Nafisa, hasHonorific, Sharifa]
Generated description
Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sharifa
Target entity description: Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
  • A. Fawzia
    Fawzia is a feminine given name most famously borne by Princess Fawzia of Egypt, a 20th-century Egyptian royal and first wife of Iran’s Shah Mohammad Reza Pahlavi.
  • 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. Habiba
    Habiba is a feminine given name commonly used in Arabic-speaking and Muslim-majority cultures, meaning "beloved" or "darling."
  • D. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • E. Buraydah
    Buraydah is a major city in central Saudi Arabia and the capital of Al-Qassim Region, known as an important agricultural and commercial center.
  • 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_69c008cf0ad4819095def81e2bd42f9f completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0643ddaa48190b3ea8061fc1d9dc4 completed March 22, 2026, 9:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64ba358748190b7c4dbf31e94b02d completed March 27, 2026, 9:19 a.m.
NEDg Description generation batch_69c64c5e5e5c8190b24aea7e4114daa5 completed March 27, 2026, 9:22 a.m.
NED2 Entity disambiguation (via description) batch_69c64da81a0881908fc5716aeb0e47fa completed March 27, 2026, 9:28 a.m.
Created at: March 22, 2026, 4:27 p.m.