Triple

T1345879
Position Surface form Disambiguated ID Type / Status
Subject Friedrich August Wolf E28569 entity
Predicate placeOfDeath P21 FINISHED
Object Marseilles E15143 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: Marseilles | Statement: [Friedrich August Wolf, placeOfDeath, Marseilles]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marseilles
Context triple: [Friedrich August Wolf, placeOfDeath, Marseilles]
  • A. Marseille chosen
    Marseille is a historic Mediterranean port city in southern France known for its diverse culture, maritime heritage, and role as a major economic hub.
  • B. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • C. Aix-en-Provence
    Aix-en-Provence is a historic and picturesque city in southern France, renowned for its Provençal charm, fountains, and as the hometown of painter Paul Cézanne.
  • D. Toulon
    Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
  • E. Montpellier
    Montpellier is a major city in southern France known for its medieval old town, vibrant university life, and proximity to the Mediterranean coast.
  • 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_69a49854eb3481908c7d56b2e449a290 completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c23e84188190b0395c57dd45b62a completed March 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69af831c25ec81908fb204000ae1b161 completed March 10, 2026, 2:34 a.m.
Created at: March 1, 2026, 7:56 p.m.