Triple

T3531697
Position Surface form Disambiguated ID Type / Status
Subject Southern France E74674 entity
Predicate includesCity P3207 FINISHED
Object Cannes E47528 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: Cannes | Statement: [Southern France, includesCity, Cannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cannes
Context triple: [Southern France, includesCity, Cannes]
  • A. Cannes chosen
    Cannes is a glamorous resort city on the French Riviera, internationally renowned for its luxury tourism, beaches, and role as a global center of the film industry.
  • B. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • C. Sophia Antipolis
    Sophia Antipolis is a major technology and research park in southeastern France, known as a European hub for telecommunications, information technology, and innovation.
  • D. Antibes
    Antibes is a historic resort town on the French Riviera known for its Mediterranean coastline, old town, and association with artists such as Pablo Picasso.
  • E. City of Nice
    The City of Nice is a major coastal city on the French Riviera, renowned for its Mediterranean climate, historic old town, and rich artistic and cultural heritage.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc988ee081909c6b9d5eed0d2d6d completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb8421b481908bda2b4f45714605 completed March 13, 2026, 7:23 a.m.
Created at: March 8, 2026, 3:19 p.m.