Triple

T4680267
Position Surface form Disambiguated ID Type / Status
Subject Alès E103781 entity
Predicate locatedIn P40 FINISHED
Object Gard department E90724 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: Gard department | Statement: [Alès, locatedIn, Gard department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gard department
Context triple: [Alès, locatedIn, Gard department]
  • A. Gard department chosen
    Gard department is an administrative region in southern France known for its Mediterranean landscapes, historic Roman sites such as the Pont du Gard, and the city of Nîmes.
  • B. Aude department
    The Aude department is an administrative region in southern France known for its historic towns, vineyards, and proximity to the Mediterranean coast.
  • C. Eure department
    The Eure department is an administrative region in northern France’s Normandy known for its rural landscapes, historic towns, and cultural sites such as Claude Monet’s garden at Giverny.
  • D. Ain department
    Ain department is an administrative region in eastern France known for its diverse landscapes, historic towns, and proximity to both the Alps and the Swiss border.
  • E. Oise department
    Oise department is an administrative division in northern France, located in the Hauts-de-France region and known for its historic towns, forests, and proximity to Paris.
  • 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_69bd43debbf08190b4bc372e286ec234 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd636c105081908655ab384f539f38 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c80125c8190b0ac3f759cce1c32 completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:16 p.m.