Triple

T2901547
Position Surface form Disambiguated ID Type / Status
Subject Eugénie Grandet E62663 entity
Predicate settingLocation P40 FINISHED
Object Saumur E229371 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: Saumur | Statement: [Eugénie Grandet, settingLocation, Saumur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saumur
Context triple: [Eugénie Grandet, settingLocation, Saumur]
  • A. Saumur chosen
    Saumur is a historic town in western France renowned for its château, wine production, and cavalry school on the banks of the Loire River.
  • B. Blois
    Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
  • C. Angoulême
    Angoulême is a historic city in southwestern France known for its hilltop old town, medieval ramparts, and status as a major center of the French comics industry.
  • D. Bourges
    Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
  • E. Châteaubriant
    Châteaubriant is a historic town in western France known for its medieval castle and role as a local administrative and cultural center.
  • 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_69ab4c3e070c8190b78d3d2c005876dd completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abe0b261c081909b66b21520b4731b completed March 7, 2026, 8:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69b5db52bcfc8190857a3ea5157d8416 completed March 14, 2026, 10:04 p.m.
Created at: March 6, 2026, 10:10 p.m.