Triple

T3928840
Position Surface form Disambiguated ID Type / Status
Subject Prime Minister of Uzbekistan E93342 entity
Predicate residesIn P75 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: [Prime Minister of Uzbekistan, residesIn, Tashkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tashkent
Context triple: [Prime Minister of Uzbekistan, residesIn, 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. Yoshkar-Ola
    Yoshkar-Ola is a city in central Russia that serves as the administrative, cultural, and economic center of the Mari El Republic.
  • E. 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.
  • 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_69aed96bfa1081908f7b30f2c647dee6 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeeda65b708190b24cd715915aec1d completed March 9, 2026, 3:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b53ff373c081908e512ba2e65fc774 completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:23 p.m.