Triple

T879877
Position Surface form Disambiguated ID Type / Status
Subject Mont Blanc massif E19000 entity
Predicate administrativeRegion P285 FINISHED
Object Valais E13342 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: Valais | Statement: [Mont Blanc massif, administrativeRegion, Valais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valais
Context triple: [Mont Blanc massif, administrativeRegion, Valais]
  • A. Valais chosen
    Valais is a mountainous canton in southwestern Switzerland known for its Alpine scenery, vineyards, and popular ski resorts such as Zermatt and Verbier.
  • B. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • C. Ile-Rousse
    Île-Rousse is a coastal town and popular seaside resort in the Balagne region of northern Corsica, known for its red granite islets and sandy beaches.
  • D. Kutaisi
    Kutaisi is one of Georgia’s major cities, historically significant and formerly a capital, located in the western part of the country.
  • E. Seeland region
    The Seeland region is an area in western Switzerland known for its lakes, fertile plains, and intensive agriculture, particularly vegetable farming.
  • 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_69a4939c32488190a7ccd41cf0abb22b completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4acc9d5f4819087afbb75b6ac3dbf completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7c726e6808190b2000051d72b434e completed March 4, 2026, 5:46 a.m.
Created at: March 1, 2026, 7:39 p.m.