Triple

T6869021
Position Surface form Disambiguated ID Type / Status
Subject Aksu E158489 entity
Predicate hasLanguageCommunity P5562 FINISHED
Object Uyghur E80070 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: Uyghur | Statement: [Aksu, hasLanguageCommunity, Uyghur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uyghur
Context triple: [Aksu, hasLanguageCommunity, Uyghur]
  • A. Uyghur language
    The Uyghur language is a Turkic language spoken primarily by the Uyghur people in China’s Xinjiang region, written in several scripts and serving as a major language of Central Asia.
  • B. Uyghurs chosen
    The Uyghurs are a Turkic-speaking, predominantly Muslim ethnic group native to the Xinjiang region of northwest China, with a distinct culture, language, and history.
  • C. Uyghur Arabic alphabet
    The Uyghur Arabic alphabet is a Perso-Arabic–based script adapted to represent the sounds of the Uyghur language, historically used by Uyghur communities in Central Asia.
  • D. Uyghur Cyrillic alphabet
    The Uyghur Cyrillic alphabet is a Cyrillic-based script historically used by Uyghur communities, particularly in the former Soviet Union, to write the Uyghur language.
  • E. Uyghur Latin alphabet
    The Uyghur Latin alphabet is a romanized writing system developed for the Uyghur language, used primarily in digital communication and linguistic transcription.
  • 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_69c68831e3648190a643c328122e4d43 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d8a916a88190b81551731dff2898 completed March 27, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c74299ae148190a56c7b1ee8829f40 completed March 28, 2026, 2:53 a.m.
Created at: March 27, 2026, 2:22 p.m.