Triple

T14788191
Position Surface form Disambiguated ID Type / Status
Subject Ulus of Jochi E347581 entity
Predicate usedTitle P3254 FINISHED
Object khan E64995 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: khan | Statement: [Ulus of Jochi, usedTitle, khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: khan
Context triple: [Ulus of Jochi, usedTitle, khan]
  • A. Khan chosen
    Khan is a common surname of Central and South Asian origin historically associated with nobility and leadership, now widely used across Muslim and other communities worldwide.
  • B. Kahn
    Kahn is a surname most famously associated with Louis Kahn, the influential 20th-century architect known for his monumental and timeless modernist buildings.
  • C. Khan Maykr
    Khan Maykr is a powerful, godlike ruler of the Maykr race and a major antagonist in Doom Eternal, orchestrating the demonic invasion of Earth.
  • D. KAHN
    KAHN is the ICAO airport code for Athens Ben Epps Airport, a public airport serving Athens, Georgia, in the United States.
  • E. Ka
    Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decaa1e9ec81908d7c26c1c4e43014 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b9e8a08190bc736ac207b77324 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.