Triple

T10257395
Position Surface form Disambiguated ID Type / Status
Subject Neisse River E240507 entity
Predicate confluenceNear P8203 FINISHED
Object Gubin E609853 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: Gubin | Statement: [Neisse River, confluenceNear, Gubin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gubin
Context triple: [Neisse River, confluenceNear, Gubin]
  • A. Gubin chosen
    Gubin is a town in western Poland situated on the Lusatian Neisse River, directly opposite the German town of Guben, forming a cross-border urban area.
  • B. Gubakha
    Gubakha is a small industrial town in Russia’s Perm Krai, historically associated with coal mining and chemical production in the Ural region.
  • C. Gongjin
    Gongjin is the courtesy name of Zhou Yu, a renowned Eastern Han dynasty military general and strategist best known for his role in the Battle of Red Cliffs.
  • D. Gubongsan
    Gubongsan is a mountain located in or near the city of Daejeon in South Korea, known for its hiking trails and scenic views.
  • E. Kwangde
    Kwangde is a prominent Himalayan mountain massif in Nepal’s Khumbu region, known for its steep faces and challenging climbing routes.
  • 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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24de4588190b68fb3daa36dbd7d completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e153b0819084708b6f7127cdea completed April 9, 2026, 12:50 a.m.
Created at: April 6, 2026, 11:31 a.m.