Triple

T6941838
Position Surface form Disambiguated ID Type / Status
Subject Digoin E160694 entity
Predicate river P165 FINISHED
Object Loire E9847 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: Loire | Statement: [Digoin, river, Loire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loire
Context triple: [Digoin, river, Loire]
  • A. Loire chosen
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • B. Loire
    Loire is a department in central-eastern France named after the Loire River, known for its varied landscapes, industrial cities like Saint-Étienne, and historical ties to the broader Loire Valley region.
  • C. Loiret
    Loiret is a department in north-central France, named after the Loiret River and known for its historic towns and proximity to the Loire Valley.
  • D. Loir
    The Loir is a river in central France that flows through the regions of Pays de la Loire and Centre-Val de Loire before joining the Sarthe.
  • E. Nièvre
    Nièvre is a rural department in central France’s Bourgogne-Franche-Comté region, known for its rolling countryside, the Loire River, and its capital city Nevers.
  • 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_69c6884f3db4819080ad65da69386206 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6da85f43881909549ac26b3db135a completed March 27, 2026, 7:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9c2dc39fc8190ae244a4077808e17 completed March 30, 2026, 12:25 a.m.
Created at: March 27, 2026, 2:28 p.m.