Triple

T8557547
Position Surface form Disambiguated ID Type / Status
Subject Princess Fahdah Mohammed Abunayyan E202610 entity
Predicate givenName P17 FINISHED
Object Fahdah
Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
 E745021 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: Fahdah | Statement: [Princess Fahdah Mohammed Abunayyan, givenName, Fahdah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fahdah
Context triple: [Princess Fahdah Mohammed Abunayyan, givenName, Fahdah]
  • A. 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.
  • B. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • C. Sharifa
    Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
  • D. المروة
    المروة هو اسم علم عربي يُستخدم غالبًا للإناث ويُستمد من اسم أحد الجبلين في شعائر السعي بين الصفا والمروة في مكة.
  • 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: Fahdah
Triple: [Princess Fahdah Mohammed Abunayyan, givenName, Fahdah]
Generated description
Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fahdah
Target entity description: Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
  • A. 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.
  • B. Juwayriya
    Juwayriya was a wife of the Prophet Muhammad and is regarded as one of the Mothers of the Believers in Islamic tradition.
  • C. Sharifa
    Sharifa is an honorific title used in Islamic tradition for a noblewoman descended from the Prophet Muhammad.
  • D. المروة
    المروة هو اسم علم عربي يُستخدم غالبًا للإناث ويُستمد من اسم أحد الجبلين في شعائر السعي بين الصفا والمروة في مكة.
  • 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_69ca8326e6c881908ff720d6abaebdc5 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe946d1408190adc7dfb7b2173f9d completed March 31, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea868de6881908e87270a1fea0e4b completed April 2, 2026, 5:33 p.m.
NEDg Description generation batch_69cea9cff1ec8190a0093fb42782341e completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaa9f7f8c8190965e86880ff141d5 completed April 2, 2026, 5:42 p.m.
Created at: March 30, 2026, 6:20 p.m.