Triple

T14912976
Position Surface form Disambiguated ID Type / Status
Subject Noor Hassanali E371308 entity
Predicate givenName P17 FINISHED
Object Noor
Noor is a given name of Arabic origin meaning "light," used for both males and females in various cultures.
 E1127163 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: [Noor Hassanali, givenName, Noor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Noor
Context triple: [Noor Hassanali, 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. Teba
    Teba is a town in the province of Málaga, Spain, historically notable as the site of a major medieval battle during the Reconquista.
  • E. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • 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: [Noor Hassanali, givenName, Noor]
Generated description
Noor is a given name of Arabic origin meaning "light," used for both males and females in various cultures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Noor
Target entity description: Noor is a given name of Arabic origin meaning "light," used for both males and females in various cultures.
  • 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. Teba
    Teba is a town in the province of Málaga, Spain, historically notable as the site of a major medieval battle during the Reconquista.
  • E. Suawa
    Suawa is an Austronesian language spoken by the Suwawa people of North Sulawesi, Indonesia.
  • 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_69d85cc7ea3481908228b5acb7d06f12 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded61d75008190b6f9a1a38137836f completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72bd18148190ab28744678c22993 completed May 8, 2026, 11:33 p.m.
NEDg Description generation batch_69fe744b9c048190ae2a64da53d8ffac completed May 8, 2026, 11:39 p.m.
NED2 Entity disambiguation (via description) batch_69fe74d510808190a2379a2380fc327e completed May 8, 2026, 11:42 p.m.
Created at: April 10, 2026, 2:27 a.m.