Triple

T10143948
Position Surface form Disambiguated ID Type / Status
Subject Abbas I E231654 entity
Predicate mother P120 FINISHED
Object Khayr al-Nisa Begum
Khayr al-Nisa Begum was a prominent Safavid royal consort and influential queen mother in early 17th-century Iran.
 E844692 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: Khayr al-Nisa Begum | Statement: [Abbas I, mother, Khayr al-Nisa Begum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Khayr al-Nisa Begum
Context triple: [Abbas I, mother, Khayr al-Nisa Begum]
  • A. Izz-un-Nissa Begum
    Izz-un-Nissa Begum was a Mughal princess and one of Emperor Shah Jahan’s wives, known for her high rank and influence within the imperial harem.
  • B. Nur-un-Nisa Begum
    Nur-un-Nisa Begum was a Mughal princess and consort of Emperor Bahadur Shah I, belonging to the imperial Timurid-Mughal royal family.
  • C. Lutf-un-nisa Begum
    Lutf-un-nisa Begum was a Mughal-era noblewoman whose name appears in historical records of the imperial court.
  • D. Zeb-un-Nissa Begum
    Zeb-un-Nissa Begum was a 17th-century Mughal princess renowned for her poetry, scholarship, and patronage of the arts in the imperial court of India.
  • E. Maham Begum
    Maham Begum was a chief consort of the Mughal emperor Babur and the mother of his successor, Humayun.
  • 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: Khayr al-Nisa Begum
Triple: [Abbas I, mother, Khayr al-Nisa Begum]
Generated description
Khayr al-Nisa Begum was a prominent Safavid royal consort and influential queen mother in early 17th-century Iran.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Khayr al-Nisa Begum
Target entity description: Khayr al-Nisa Begum was a prominent Safavid royal consort and influential queen mother in early 17th-century Iran.
  • A. Izz-un-Nissa Begum
    Izz-un-Nissa Begum was a Mughal princess and one of Emperor Shah Jahan’s wives, known for her high rank and influence within the imperial harem.
  • B. Nur-un-Nisa Begum
    Nur-un-Nisa Begum was a Mughal princess and consort of Emperor Bahadur Shah I, belonging to the imperial Timurid-Mughal royal family.
  • C. Lutf-un-nisa Begum
    Lutf-un-nisa Begum was a Mughal-era noblewoman whose name appears in historical records of the imperial court.
  • D. Zeb-un-Nissa Begum
    Zeb-un-Nissa Begum was a 17th-century Mughal princess renowned for her poetry, scholarship, and patronage of the arts in the imperial court of India.
  • E. Maham Begum
    Maham Begum was a chief consort of the Mughal emperor Babur and the mother of his successor, Humayun.
  • 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_69ca848364f881908a24366a6feec1db completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdeb28a1708190b46499dbe51a694a completed April 2, 2026, 4:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e618b0bc8190bc1d6f15dac2708e completed April 5, 2026, 10:45 p.m.
NEDg Description generation batch_69d2e866cc4881909b5f4d1502a69885 completed April 5, 2026, 10:55 p.m.
NED2 Entity disambiguation (via description) batch_69d2e91061248190a7f9022c26daba0e completed April 5, 2026, 10:58 p.m.
Created at: March 30, 2026, 9:07 p.m.