Triple

T4228870
Position Surface form Disambiguated ID Type / Status
Subject Lauterbrunnen Valley E94527 entity
Predicate hasVillage P4011 FINISHED
Object Mürren E102976 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: Mürren | Statement: [Lauterbrunnen Valley, hasVillage, Mürren]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mürren
Context triple: [Lauterbrunnen Valley, hasVillage, Mürren]
  • A. Mürren chosen
    Mürren is a traditional, car-free mountain village and popular ski resort perched high above the Lauterbrunnen Valley in the Swiss Bernese Alps.
  • B. Wengen
    Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
  • C. Gimmelwald
    Gimmelwald is a small, traditional Swiss alpine village known for its dramatic mountain scenery and tranquil, car-free atmosphere in the Bernese Oberland.
  • D. Adelboden
    Adelboden is a Swiss alpine village and ski resort in the Bernese Oberland, known for its mountain scenery and World Cup ski races.
  • E. Kandersteg
    Kandersteg is a Swiss mountain village and popular tourist resort known for its scenic alpine landscapes, hiking trails, and access to Lake Oeschinen.
  • 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_69b3453700a08190ae88792e3dc63207 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e51817c8190bff50f2c3b5deea0 completed March 12, 2026, 11:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69b63725b9348190af56a6b7477de03f completed March 15, 2026, 4:35 a.m.
Created at: March 12, 2026, 11:04 p.m.