Triple

T3796472
Position Surface form Disambiguated ID Type / Status
Subject China United Airlines E89780 entity
Predicate cityServed P82 FINISHED
Object Urumqi E185771 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: Urumqi | Statement: [China United Airlines, cityServed, Urumqi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urumqi
Context triple: [China United Airlines, cityServed, Urumqi]
  • A. Urumqi chosen
    Urumqi is the capital of China’s Xinjiang Uyghur Autonomous Region, known as a major cultural and economic hub in Central Asia and one of the most inland major cities in the world.
  • B. Yining
    Yining is a city in the Ili Kazakh Autonomous Prefecture of far northwestern China, known for its diverse ethnic population and role as a regional trade and cultural center.
  • C. Kashgar
    Kashgar is an ancient oasis city in western China’s Xinjiang region that long served as a key cultural and commercial crossroads between East and West.
  • D. Hohhot
    Hohhot is the capital and largest city of Inner Mongolia in northern China, known as a regional center of politics, culture, and industry.
  • E. Karamay
    Karamay is an oil-rich industrial city in northwestern China known for its major petroleum fields and role in the energy industry of Xinjiang.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79f09bc8190b7514a11a030eba5 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f05ea5e081908c4714ca35aed48b completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.