Triple

T621767
Position Surface form Disambiguated ID Type / Status
Subject Caroline Bonaparte E14528 entity
Predicate placeOfBirth P1 FINISHED
Object Ajaccio E22361 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: Ajaccio | Statement: [Caroline Bonaparte, placeOfBirth, Ajaccio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ajaccio
Context triple: [Caroline Bonaparte, placeOfBirth, Ajaccio]
  • A. Ajaccio chosen
    Ajaccio is a coastal city on the French island of Corsica, best known as the birthplace of Napoleon Bonaparte and now a popular Mediterranean tourist destination.
  • B. Marseille
    Marseille is a historic Mediterranean port city in southern France known for its diverse culture, maritime heritage, and role as a major economic hub.
  • C. Aigues-Mortes
    Aigues-Mortes is a historic fortified town in southern France, renowned for its well-preserved medieval walls and proximity to the salt marshes of the Camargue.
  • 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. Saint-Tropez
    Saint-Tropez is a coastal town on the French Riviera, famed as a glamorous Mediterranean resort and former artists’ haven.
  • 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_69a4934b17c881909ace8270e8ddd202 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49e3e5d80819096e72e11b533f931 completed March 1, 2026, 8:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7f1e0cd48190953a1e0dc2912e39 completed March 7, 2026, 7:40 p.m.
Created at: March 1, 2026, 7:35 p.m.