Triple

T21299997
Position Surface form Disambiguated ID Type / Status
Subject Gorzów Wielkopolski E525032 entity
Predicate twinCity P1072 FINISHED
Object Sumy NE NERFINISHED

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: Sumy | Statement: [Gorzów Wielkopolski, twinCity, Sumy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sumy
Context triple: [Gorzów Wielkopolski, twinCity, Sumy]
  • A. Sumy chosen
    Sumy is a regional city in northeastern Ukraine known as the administrative center of Sumy Oblast and an important cultural, educational, and industrial hub.
  • B. Rivne
    Rivne is a city in western Ukraine that serves as an important regional administrative, economic, and cultural center.
  • C. Ternopil
    Ternopil is a city in western Ukraine known as a regional cultural and economic center with a historic old town and a picturesque lakeside setting.
  • D. Uzhhorod
    Uzhhorod is a historic city in western Ukraine near the Slovak and Hungarian borders, known for its multicultural heritage and as the administrative center of Zakarpattia Oblast.
  • E. Khmelnytskyi
    Khmelnytskyi is a regional city in western Ukraine known as an important administrative, economic, and cultural center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385b1c548190b940ded0163ee3ca completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:05 p.m.