Triple

T6340684
Position Surface form Disambiguated ID Type / Status
Subject Morbihan E142615 entity
Predicate capital P234 FINISHED
Object Vannes E162998 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: Vannes | Statement: [Morbihan, capital, Vannes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vannes
Context triple: [Morbihan, capital, Vannes]
  • A. Vannes chosen
    Vannes is a historic coastal city in northwestern France known for its well-preserved medieval old town and harbor on the Gulf of Morbihan.
  • B. Quimper
    Quimper is a historic city in western France known for its medieval old town, Gothic cathedral, and traditional Breton culture.
  • C. Rennes
    Rennes is the capital city of France’s Brittany region, known for its historic medieval center, vibrant student population, and role as a major cultural and economic hub in western France.
  • D. Le Croisic
    Le Croisic is a coastal town and popular seaside resort on the Atlantic coast of western France, known for its historic harbor and scenic peninsula.
  • E. Concarneau
    Concarneau is a coastal town and fishing port in Brittany, France, known for its walled medieval "Ville Close" and maritime heritage.
  • 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_69c008d5ab108190b346c465696824a9 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c0674311388190bb069a07a7ff60ef completed March 22, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6043afb4081908d480ad868625909 completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.