Triple

T15447898
Position Surface form Disambiguated ID Type / Status
Subject La Côte wine region E370071 entity
Predicate influencedBy P9 FINISHED
Object Lake Geneva E8337 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: Lake Geneva | Statement: [La Côte wine region, influencedBy, Lake Geneva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Geneva
Context triple: [La Côte wine region, influencedBy, Lake Geneva]
  • A. Lake Geneva chosen
    Lake Geneva is a large crescent-shaped lake on the north side of the Alps, shared by Switzerland and France and renowned for its scenic beauty and surrounding cities like Geneva and Lausanne.
  • B. Geneva Lake
    Geneva Lake is a popular glacial lake in southeastern Wisconsin known for its resort communities, recreational boating, and scenic shoreline.
  • C. Lake of Gruyère
    Lake of Gruyère is an artificial reservoir in the Swiss canton of Fribourg, known for its scenic setting amid pre-Alpine landscapes and the nearby medieval town of Gruyères.
  • D. Lake Lucerne
    Lake Lucerne is a residential community in Miami Gardens, Florida, known for its suburban character within the Miami metropolitan area.
  • E. Lake Lucerne
    Lake Lucerne is a picturesque, fjord-like lake in central Switzerland, renowned for its dramatic mountain scenery, historic sites, and role as a major tourist destination.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef767b4819099f2c0919a158321 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff364bafd0819086b8aab1c216c6fa completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:21 a.m.