Triple

T5250447
Position Surface form Disambiguated ID Type / Status
Subject Eiger E118572 entity
Predicate visibleFrom P1165 FINISHED
Object Grindelwald E89932 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: Grindelwald | Statement: [Eiger, visibleFrom, Grindelwald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grindelwald
Context triple: [Eiger, visibleFrom, Grindelwald]
  • A. Grindelwald chosen
    Grindelwald is a Swiss mountain village and popular alpine resort known for its dramatic scenery, skiing, and hiking in the Bernese Oberland region.
  • B. Nottwil
    Nottwil is a Swiss municipality in the canton of Lucerne, known for its lakeside location and the Swiss Paraplegic Centre.
  • C. Ferragus
    Ferragus is a novel by Honoré de Balzac that forms part of his La Comédie humaine cycle, depicting the secretive underworld and social intrigues of Parisian life.
  • D. Aue
    Aue is a town in the Ore Mountains region of Saxony, Germany, known historically for its mining industry and role as a local transport hub.
  • E. Murnau Moor
    Murnau Moor is a large, ecologically significant bog and nature reserve in Bavaria, Germany, known for its unique wetland landscapes and biodiversity.
  • 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_69bd4468aacc8190a8196f71855cdf4f completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7b79ae0c81908a9b8614f6886259 completed March 20, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf06bc1c0c8190abc1e24f99621e49 completed March 21, 2026, 8:59 p.m.
Created at: March 20, 2026, 1:50 p.m.