Triple

T18501032
Position Surface form Disambiguated ID Type / Status
Subject Bernmobil E452064 entity
Predicate hasAbbreviation P43 FINISHED
Object BERNMOBIL 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: BERNMOBIL | Statement: [Bernmobil, hasAbbreviation, BERNMOBIL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: BERNMOBIL
Context triple: [Bernmobil, hasAbbreviation, BERNMOBIL]
  • A. Bernmobil chosen
    Bernmobil is the public transport company responsible for operating trams, buses, and other urban transit services in the Swiss city of Bern.
  • B. Berner
    A Berner is a resident or native of the Swiss city of Bern.
  • C. Berner
    Berner is an American rapper and entrepreneur known for his prolific collaborations in hip-hop and his influential role in the legal cannabis industry.
  • D. Brugg AG
    Brugg AG is a municipality in the canton of Aargau in northern Switzerland, known as a regional transport hub and local economic center.
  • E. Berner Oberland-Bahnen AG
    Berner Oberland-Bahnen AG is a Swiss railway company that operates regional and tourist rail services in the Bernese Oberland region, including routes to popular alpine destinations.
  • 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_69d8d3855d50819097fc8561b0299dd9 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e532c43de48190b49b87c1bb591016 completed April 19, 2026, 7:53 p.m.
Created at: April 10, 2026, 11:36 a.m.