Triple

T3531698
Position Surface form Disambiguated ID Type / Status
Subject Southern France E74674 entity
Predicate includesCity P3207 FINISHED
Object Saint-Tropez E64451 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: Saint-Tropez | Statement: [Southern France, includesCity, Saint-Tropez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saint-Tropez
Context triple: [Southern France, includesCity, Saint-Tropez]
  • A. Saint-Tropez chosen
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • B. Cagnes-sur-Mer
    Cagnes-sur-Mer is a coastal town on the French Riviera in southeastern France, known for its Mediterranean beaches and historic hilltop village.
  • C. 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.
  • D. Juan-les-Pins
    Juan-les-Pins is a seaside resort town on the French Riviera, known for its beaches, nightlife, and jazz festival.
  • E. Saint-Brevin-les-Pins
    Saint-Brevin-les-Pins is a seaside commune on France’s Atlantic coast, known for its sandy beaches, pine forests, and role as a gateway to the Loire estuary opposite Saint-Nazaire.
  • 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_69bda3f5a8a88190a494a9338c01962a completed March 20, 2026, 7:45 p.m.
Created at: March 8, 2026, 3:19 p.m.