Triple

T8737175
Position Surface form Disambiguated ID Type / Status
Subject Astrakhan Khanate E207414 entity
Predicate rulerTitle P593 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: [Astrakhan Khanate, rulerTitle, khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: khan
Context triple: [Astrakhan Khanate, rulerTitle, 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. KAHN
    KAHN is the ICAO airport code for Athens Ben Epps Airport, a public airport serving Athens, Georgia, in the United States.
  • D. Ka
    Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d45c96081909aa8509064ff3a04 completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42c9140081909f9c10560757c860 completed April 3, 2026, 4:32 a.m.
Created at: March 30, 2026, 6:38 p.m.