Triple

T12678367
Position Surface form Disambiguated ID Type / Status
Subject Memel River E302880 entity
Predicate hasMajorCityOnBank P7935 FINISHED
Object Grodno E54772 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: Grodno | Statement: [Memel River, hasMajorCityOnBank, Grodno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grodno
Context triple: [Memel River, hasMajorCityOnBank, Grodno]
  • A. Novopolotsk
    Novopolotsk is an industrial city in northern Belarus known for its major oil refinery and petrochemical complex.
  • B. Vitebsk
    Vitebsk is a historic city in northeastern Belarus known as a major cultural center and the birthplace of artist Marc Chagall.
  • C. Hrodna chosen
    Hrodna is a historic city in western Belarus known for its well-preserved architecture and role as a major cultural and economic center of the region.
  • D. Vilna
    Vilna is the historical name for Vilnius, the capital city of Lithuania and a major cultural and political center of the region.
  • E. Polotsk
    Polotsk is one of the oldest cities in Belarus, historically a major political, cultural, and religious center of the medieval East Slavic world.
  • 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_69d7bdee64a08190801c6d470aefd723 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961b1dff48190923290555ece5d89 completed April 10, 2026, 8:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbb4d0088190b71fc0573cd40ddd completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 5:20 p.m.