Triple

T6108436
Position Surface form Disambiguated ID Type / Status
Subject Borjigin E136172 entity
Predicate hasNotableMember P304 FINISHED
Object Kublai Khan E25319 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: Kublai Khan | Statement: [Borjigin, hasNotableMember, Kublai Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kublai Khan
Context triple: [Borjigin, hasNotableMember, Kublai Khan]
  • A. Kublai Khan chosen
    Kublai Khan was the 13th-century Mongol emperor who founded China’s Yuan dynasty and presided over one of the largest empires in history.
  • B. Yesün Temür
    Yesün Temür was a 14th-century Mongol ruler who served as Great Khan of the Mongol Empire and emperor of the Yuan dynasty in China.
  • C. Toghon Temür
    Toghon Temür was the last emperor of the Yuan dynasty in China, whose troubled reign ended with the dynasty’s collapse and the rise of the Ming.
  • D. Güyük Khan
    Güyük Khan was the third Great Khan of the Mongol Empire, ruling briefly in the 1240s and known for consolidating Mongol authority while facing internal dynastic tensions.
  • E. Möngke Khan
    Möngke Khan was the fourth Great Khan of the Mongol Empire, under whose rule the empire reached its greatest territorial extent and saw major administrative and fiscal reforms.
  • 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_69c0087dee9881909e3655be88208c01 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05b835ed48190971c3ba397ca329f completed March 22, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1255f03e08190b62cd8ca2c079afb completed March 23, 2026, 11:34 a.m.
Created at: March 22, 2026, 4:13 p.m.