Triple

T15085847
Position Surface form Disambiguated ID Type / Status
Subject Fortifications of Marseille E360269 entity
Predicate governedBy P46 FINISHED
Object City of Marseille 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: City of Marseille | Statement: [Fortifications of Marseille, governedBy, City of Marseille]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Marseille
Context triple: [Fortifications of Marseille, governedBy, City of Marseille]
  • 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. Marseillan
    Marseillan is a coastal commune in southern France known for its historic port, oyster farming, and proximity to the Étang de Thau lagoon.
  • C. 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.
  • D. Toulon
    Toulon is a major port city on France’s Mediterranean coast that serves as the principal base of the French Navy.
  • E. La Ciotat
    La Ciotat is a coastal town on the Mediterranean in southern France, known for its historic shipyards and as one of the birthplaces of early cinema through the Lumière brothers’ pioneering films.
  • 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_69d85a035aa88190b52a139d3a1b7b6d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00275cfa88190a13fe20b585d9fcb completed April 15, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b340900819093aa210b702f124b completed May 9, 2026, 10:23 a.m.
Created at: April 10, 2026, 3:03 a.m.