Triple

T7415965
Position Surface form Disambiguated ID Type / Status
Subject German occupation of Ukraine E171130 entity
Predicate location 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: [German occupation of Ukraine, location, Kharkiv]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kharkiv
Context triple: [German occupation of Ukraine, location, 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. 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.
  • D. Kyiv
    Kyiv is the capital and largest city of Ukraine, serving as its political, cultural, and economic center.
  • E. Chernihiv
    Chernihiv is a historic city in northern Ukraine known for its ancient churches, rich cultural heritage, and role as a regional administrative and memorial 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_69c68a618bdc81908d8018edadecd1a4 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2c643248190a387abba2f482b25 completed March 27, 2026, 9:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c82779a1d8819098f136291fa42433 completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:11 p.m.