Triple

T13923084
Position Surface form Disambiguated ID Type / Status
Subject Umar Shaikh Mirza I E334793 entity
Predicate mother P120 FINISHED
Object Tolun Agha
Tolun Agha was the mother of Timurid prince Umar Shaikh Mirza I and a consort within the Timurid royal household.
E1078539 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: Tolun Agha | Statement: [Umar Shaikh Mirza I, mother, Tolun Agha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tolun Agha
Context triple: [Umar Shaikh Mirza I, mother, Tolun Agha]
  • A. Agha Begi Agha
    Agha Begi Agha was a consort of the Timurid ruler and renowned astronomer Ulugh Beg in 15th-century Central Asia.
  • B. Ibrahim Agha
    Ibrahim Agha was an Ottoman military commander known for leading resistance against the French forces during their 1830 landing at Sidi Ferruch near Algiers.
  • C. Mirza Isa Tarkhan
    Mirza Isa Tarkhan was a ruler of the Tarkhan dynasty in Sindh, known for governing the region during the late 16th century amid the expanding influence of the Mughal Empire.
  • D. Raza Murad
    Raza Murad is an Indian character actor known for his deep voice and frequent portrayals of villains and authoritative figures in Hindi cinema.
  • E. Hasan Bughra Khan
    Hasan Bughra Khan was a prominent ruler of the Kara-Khanid dynasty, known for consolidating its power in Central Asia during the late 10th 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: Tolun Agha
Triple: [Umar Shaikh Mirza I, mother, Tolun Agha]
Generated description
Tolun Agha was the mother of Timurid prince Umar Shaikh Mirza I and a consort within the Timurid royal household.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tolun Agha
Target entity description: Tolun Agha was the mother of Timurid prince Umar Shaikh Mirza I and a consort within the Timurid royal household.
  • A. Agha Begi Agha
    Agha Begi Agha was a consort of the Timurid ruler and renowned astronomer Ulugh Beg in 15th-century Central Asia.
  • B. Ibrahim Agha
    Ibrahim Agha was an Ottoman military commander known for leading resistance against the French forces during their 1830 landing at Sidi Ferruch near Algiers.
  • C. Mirza Isa Tarkhan
    Mirza Isa Tarkhan was a ruler of the Tarkhan dynasty in Sindh, known for governing the region during the late 16th century amid the expanding influence of the Mughal Empire.
  • D. Raza Murad
    Raza Murad is an Indian character actor known for his deep voice and frequent portrayals of villains and authoritative figures in Hindi cinema.
  • E. Hasan Bughra Khan
    Hasan Bughra Khan was a prominent ruler of the Kara-Khanid dynasty, known for consolidating its power in Central Asia during the late 10th century.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa5c1f481908a9d8786872f08fe completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcb64c5644819086e1bdbb5132779d completed May 7, 2026, 3:57 p.m.
NEDg Description generation batch_69fcc6819fa08190b8d403c9233cf0e1 completed May 7, 2026, 5:06 p.m.
NED2 Entity disambiguation (via description) batch_69fcc73137b88190838b5845b67f64c1 completed May 7, 2026, 5:09 p.m.
Created at: April 9, 2026, 10:16 p.m.