Triple

T2962019
Position Surface form Disambiguated ID Type / Status
Subject Uyghurs E80070 entity
Predicate majorCity P316 FINISHED
Object Hotan E128870 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: Hotan | Statement: [Uyghurs, majorCity, Hotan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hotan
Context triple: [Uyghurs, majorCity, Hotan]
  • A. Hotan chosen
    Hotan is an oasis city in southwestern Xinjiang, China, historically known as a key Silk Road hub famed for its jade, silk, and carpets.
  • B. Aksu
    Aksu is a city in northwestern China’s Xinjiang Uyghur Autonomous Region, known as an important oasis and agricultural center along the historic Silk Road.
  • 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. Korla
    Korla is a major oasis city in Xinjiang, China, known as an important transportation and economic hub along the northern edge of the Taklamakan Desert.
  • 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_69ad8b1341848190bd19dbf46892887d completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9955e6488190bea170724d5fbfe8 completed March 8, 2026, 3:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69b0fc959b3c8190a0d95a3e616246f9 completed March 11, 2026, 5:24 a.m.
Created at: March 8, 2026, 2:57 p.m.