Triple

T1841642
Position Surface form Disambiguated ID Type / Status
Subject Tours E41188 entity
Predicate isPrefectureOf P3877 FINISHED
Object Indre-et-Loire E138241 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: Indre-et-Loire | Statement: [Tours, isPrefectureOf, Indre-et-Loire]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indre-et-Loire
Context triple: [Tours, isPrefectureOf, Indre-et-Loire]
  • A. Indre-et-Loire chosen
    Indre-et-Loire is a department in central France known for its historic châteaux, vineyards, and the city of Tours in the Loire Valley.
  • B. Loir-et-Cher
    Loir-et-Cher is a department in central France known for its historic châteaux, including parts of the Loire Valley UNESCO World Heritage site.
  • C. Sarthe
    Sarthe is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • D. Essonne
    Essonne is a department in northern France that forms part of the Paris metropolitan region and includes a mix of suburban communities, research centers, and rural areas.
  • E. Saône-et-Loire
    Saône-et-Loire is a department in the Bourgogne-Franche-Comté region of eastern France, known for its historic towns, Romanesque churches, and Burgundy vineyards.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb03e7a7481909c5b902034390ef1 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c482908190b940497fc5d5db60 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:33 p.m.