Triple

T1276089
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan France E27215 entity
Predicate hasRiver 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: [Metropolitan France, hasRiver, Loire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Loire
Context triple: [Metropolitan France, hasRiver, Loire]
  • A. Loire chosen
    The Loire is the longest river in France, renowned for its scenic valley dotted with historic châteaux and vineyards.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Rive Droite
    Rive Droite is the northern, historically affluent bank of the Seine in Paris, known for its grand boulevards, major museums, and iconic landmarks.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c08ef32c8190a493c8215946e5dd completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69adeab797c48190a3a2f7313638f594 completed March 8, 2026, 9:31 p.m.
Created at: March 1, 2026, 7:50 p.m.