Triple

T9505452
Position Surface form Disambiguated ID Type / Status
Subject Sarthe E229256 entity
Predicate contains P35 FINISHED
Object Allonnes E410220 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: Allonnes | Statement: [Sarthe, contains, Allonnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allonnes
Context triple: [Sarthe, contains, Allonnes]
  • A. Allonnes chosen
    Allonnes is a commune in western France, known as a residential suburb of Le Mans with a mix of industrial areas and green spaces.
  • B. Escoutoux
    Escoutoux is a small commune in central France’s Puy-de-Dôme department, known for its rural setting in the Auvergne region.
  • C. Charpennes
    Charpennes is a prominent urban district in the Lyon metropolitan area, known for its major transport hub and dense residential and commercial activity.
  • D. Douaumont
    Douaumont is a small commune in northeastern France best known for its World War I battlefield sites near Verdun, including major memorials and military cemeteries.
  • E. Weiler-la-Tour
    Weiler-la-Tour is a small commune and village in southeastern Luxembourg, known for its rural character and proximity to the capital city, Luxembourg City.
  • 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9850fe6c8190a5a96cfae12562c6 completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1af37e78081909683ce5359a8eb0e completed April 5, 2026, 12:39 a.m.
Created at: March 30, 2026, 7:57 p.m.