Triple

T3373526
Position Surface form Disambiguated ID Type / Status
Subject Taj Mahal Begum E71010 entity
Predicate title P38 FINISHED
Object Begum E106849 NE FINISHED

How this triple was built (2 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: Begum | Statement: [Taj Mahal Begum, title, Begum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Begum
Context triple: [Taj Mahal Begum, title, Begum]
  • A. Begum chosen
    Begum is an honorific title historically used in South Asia for Muslim women of high social rank, especially queens, princesses, and noblewomen.
  • B. Kandahari Begum
    Kandahari Begum was a Mughal princess and the first wife of Emperor Shah Jahan, known for her Timurid lineage and political significance in the Mughal court.
  • C. Khanzada Begum
    Khanzada Begum was a Timurid princess and elder sister of Mughal emperor Babur, noted for her political marriages and influential role in early Mughal diplomacy.
  • D. Haji Begum
    Haji Begum was a Mughal empress and chief consort of Emperor Humayun, best known for overseeing the construction of his grand mausoleum in Delhi.
  • E. Dilras Banu Begum
    Dilras Banu Begum was a 17th-century Mughal princess and the chief consort of Emperor Aurangzeb, remembered as the mother of several of his children and for the grand mausoleum Bibi Ka Maqbara built in her memory.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ad85a7f80c8190a05e43013f298942 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb2bdcf70819087fc7e00fbd61e0d completed March 8, 2026, 5:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69b432f118f48190a81795289a20efe5 completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:13 p.m.