Triple

T7913413
Position Surface form Disambiguated ID Type / Status
Subject Princess Noor bint Hamzah E183755 entity
Predicate givenName P17 FINISHED
Object Noor
Noor is a Jordanian princess and member of the Hashemite royal family.
 E122857 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: Noor | Statement: [Princess Noor bint Hamzah, givenName, Noor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Noor
Context triple: [Princess Noor bint Hamzah, givenName, Noor]
  • A. Noor
    Noor is the American-born widow of King Hussein who served as Queen consort of Jordan and became known for her humanitarian and peace-building work.
  • B. Noor
    Noor is a science fiction novel by Nnedi Okorafor that blends Africanfuturism with themes of identity, technology, and survival in a near-future Nigeria.
  • C. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • D. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • E. Bawi
    Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
  • 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: Noor
Triple: [Princess Noor bint Hamzah, givenName, Noor]
Generated description
Noor is a Jordanian princess and member of the Hashemite royal family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Noor
Target entity description: Noor is a Jordanian princess and member of the Hashemite royal family.
  • A. Noor chosen
    Noor is the American-born widow of King Hussein who served as Queen consort of Jordan and became known for her humanitarian and peace-building work.
  • B. Noor
    Noor is a science fiction novel by Nnedi Okorafor that blends Africanfuturism with themes of identity, technology, and survival in a near-future Nigeria.
  • C. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • D. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • E. Bawi
    Bawi was a Sasanian Persian military commander known for leading forces against the Byzantine Empire during the Iberian War in the 6th century.
  • F. None of above.

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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a748f4c8190bcd868de2fcf0b3a completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bdfb8d0819089cf1268df61bcdc completed March 31, 2026, 5:30 a.m.
NEDg Description generation batch_69cb5f20eb3c81909e059d5a02263aa2 completed March 31, 2026, 5:44 a.m.
NED2 Entity disambiguation (via description) batch_69cb76bb9a308190a9d7b34838d696db completed March 31, 2026, 7:24 a.m.
Created at: March 30, 2026, 5:04 p.m.