Triple

T955174
Position Surface form Disambiguated ID Type / Status
Subject Radio Free Europe/Radio Liberty E20608 entity
Predicate hasOfficeIn P1268 FINISHED
Object Tashkent E81695 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: Tashkent | Statement: [Radio Free Europe/Radio Liberty, hasOfficeIn, Tashkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tashkent
Context triple: [Radio Free Europe/Radio Liberty, hasOfficeIn, Tashkent]
  • A. Tashkent chosen
    Tashkent is the capital and largest city of Uzbekistan, a major cultural and economic hub in Central Asia with deep historical ties to the Islamic world.
  • B. Nukus
    Nukus is the capital of the autonomous Republic of Karakalpakstan in western Uzbekistan, known for its remote desert location and the renowned Nukus Museum of Art.
  • C. Navoi
    Navoi is an industrial city in central Uzbekistan known for its mining, metallurgy, and chemical industries.
  • D. Bishkek
    Bishkek is the largest city and political, economic, and cultural center of Kyrgyzstan, located in the north of the country near the Kyrgyz Ala-Too mountain range.
  • E. Andijan
    Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
  • 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_69a493b21f2881908132dcf45dcd2f36 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b3f7a7608190b8a8dd2486654bec completed March 1, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c017e148190b368419cff3872f6 completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:40 p.m.