Triple

T30309775
Position Surface form Disambiguated ID Type / Status
Subject Berezina Biosphere Reserve E770890 entity
Predicate locatedIn P40 FINISHED
Object Dokshytsy District
Dokshytsy District is an administrative district in Belarus known for encompassing part of the ecologically significant Berezina Biosphere Reserve.
E2198681 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: Dokshytsy District | Statement: [Berezina Biosphere Reserve, locatedIn, Dokshytsy District]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Dokshytsy District
Triple: [Berezina Biosphere Reserve, locatedIn, Dokshytsy District]
Generated description
Dokshytsy District is an administrative district in Belarus known for encompassing part of the ecologically significant Berezina Biosphere Reserve.

Provenance (5 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_69f22488f224819081b0f3ec41ab975c completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6816af64c819085ab7959e7d902cd completed May 2, 2026, 10:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3d177501388190a7d78134fcc01336 completed June 25, 2026, 11:56 a.m.
NEDg Description generation batch_6a3d181234f48190bff484199a3adc82 completed June 25, 2026, 11:59 a.m.
NED2 Entity disambiguation (via description) batch_6a3d6383a6848190beddf32135d0b6e5 completed June 25, 2026, 5:21 p.m.
Created at: April 29, 2026, 7:50 p.m.