Triple

T9182156
Position Surface form Disambiguated ID Type / Status
Subject Kharkiv National University of Radioelectronics E220357 entity
Predicate locatedIn P40 FINISHED
Object Kharkiv E38108 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: Kharkiv | Statement: [Kharkiv National University of Radioelectronics, locatedIn, Kharkiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kharkiv
Context triple: [Kharkiv National University of Radioelectronics, locatedIn, Kharkiv]
  • A. Kharkiv chosen
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • B. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • C. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • D. Dnipro
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • E. Kyiv
    Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
  • 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_69ca83e589948190ac9907819db11ddf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccc25379008190b8ca047efe3bb7bb completed April 1, 2026, 6:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d5f2bfdc5881909689a8b24d605458 completed April 8, 2026, 6:16 a.m.
Created at: March 30, 2026, 7:23 p.m.