Triple

T14783432
Position Surface form Disambiguated ID Type / Status
Subject Linach E347449 entity
Predicate mouthLocation P417 FINISHED
Object Breg E69261 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: Breg | Statement: [Linach, mouthLocation, Breg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Breg
Context triple: [Linach, mouthLocation, Breg]
  • A. Breg chosen
    Breg is a river in Germany’s Black Forest region that forms one of the main headwaters of the Danube.
  • B. Breage
    Breage is a rural village and civil parish in west Cornwall, England, known for its historic church and traditional Cornish mining heritage.
  • C. Brey
    Brey is the paternal surname of Spanish politician Mariano Rajoy Brey, who served as Prime Minister of Spain from 2011 to 2018.
  • D. Breng
    Breng is a Dutch public transport operator providing regional bus and train services in and around Arnhem and Nijmegen in the Netherlands.
  • E. Bongrand
    Bongrand is a fictional character in Émile Zola’s novel *L’Œuvre*, depicted as an older, established painter who contrasts with the avant-garde ambitions of the protagonist.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deca9f1c9c8190a8b28ba0ddd3e2e3 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24b626c48190a6aa9eda43539246 completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:31 a.m.