Triple

T3491371
Position Surface form Disambiguated ID Type / Status
Subject French Riviera E73737 entity
Predicate contains P35 FINISHED
Object Cap d’Antibes E65894 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: Cap d’Antibes | Statement: [French Riviera, contains, Cap d’Antibes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cap d’Antibes
Context triple: [French Riviera, contains, Cap d’Antibes]
  • A. Antibes chosen
    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.
  • B. Fréjus
    Fréjus is a historic town and seaside resort on the French Riviera in southeastern France, known for its Roman ruins and Mediterranean coastline.
  • C. Frontignan
    Frontignan is a coastal commune in southern France known for its Muscat wine production and Mediterranean setting near Sète.
  • D. Leucate
    Leucate is a coastal commune in southern France known for its Mediterranean beaches, wind sports, and scenic limestone cliffs.
  • E. Le Cannet
    Le Cannet is a commune in the Alpes-Maritimes department of southeastern France, located just north of Cannes on the French Riviera.
  • 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_69ad85cca8d4819088494e9f3340fab5 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbaa720c8190af47b052cc66c225 completed March 8, 2026, 6:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bb7a4e5481908322a2f0c1bf8119 completed March 13, 2026, 7:23 a.m.
Created at: March 8, 2026, 3:18 p.m.