Triple

T17150692
Position Surface form Disambiguated ID Type / Status
Subject Arinsal E416212 entity
Predicate partOf P40 FINISHED
Object Vallnord ski area E912014 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: Vallnord ski area | Statement: [Arinsal, partOf, Vallnord ski area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vallnord ski area
Context triple: [Arinsal, partOf, Vallnord ski area]
  • A. Vallnord ski area chosen
    Vallnord ski area is a popular ski and snowboard resort complex in Andorra known for its varied slopes, modern facilities, and family-friendly winter sports offerings.
  • B. Brunni ski area
    Brunni ski area is a family-friendly ski and hiking resort above Engelberg in central Switzerland, known for its sunny slopes and views of the surrounding Alps.
  • C. Storlien ski area
    Storlien ski area is a Swedish alpine resort near the Norwegian border known for its downhill skiing, cross-country trails, and mountain scenery.
  • D. Kvitfjell ski resort
    Kvitfjell ski resort is a Norwegian alpine skiing destination renowned for its Olympic-standard downhill courses and regular FIS World Cup races.
  • E. Ålsheia ski resort
    Ålsheia ski resort is a popular alpine skiing destination in Sirdal, Norway, known for its varied slopes and winter sports facilities.
  • 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_69d886d279c081909f8ff1f743ddeb69 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f4067470819084aa233c4c4a6d4f completed April 18, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fc46c308190b09efb13776747e7 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:36 a.m.