Triple

T10870540
Position Surface form Disambiguated ID Type / Status
Subject Uri E256636 entity
Predicate hasMunicipality P847 FINISHED
Object Andermatt E425655 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: Andermatt | Statement: [Uri, hasMunicipality, Andermatt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andermatt
Context triple: [Uri, hasMunicipality, Andermatt]
  • A. Andermatt chosen
    Andermatt is a Swiss Alpine village and ski resort in the canton of Uri, known as a major mountain transport hub and tourist destination.
  • B. Wengen
    Wengen is a car-free Swiss alpine village and popular ski and hiking resort located in the Bernese Oberland region.
  • C. Arosa
    Arosa is a Swiss alpine resort town in the canton of Graubünden, known for its skiing, hiking, and scenic mountain landscapes.
  • D. Visp
    Visp is a small town in the canton of Valais in southwestern Switzerland, situated in the Rhône valley and known as a regional transport hub and gateway to nearby Alpine resorts.
  • 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_69d6aa83d1448190a66d93c32394d21f completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d7518610e48190bee50db71ae0ca3e completed April 9, 2026, 7:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7d9ce3c8190afeb2a27fb82b594 completed April 15, 2026, 8:40 p.m.
Created at: April 8, 2026, 9:20 p.m.