Triple

T17117627
Position Surface form Disambiguated ID Type / Status
Subject Vienne E415380 entity
Predicate flowsThrough P225 FINISHED
Object city of Limoges E49689 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: city of Limoges | Statement: [Vienne, flowsThrough, city of Limoges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Limoges
Context triple: [Vienne, flowsThrough, city of Limoges]
  • A. Limoges chosen
    Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
  • B. Limoges urban area
    The Limoges urban area is a metropolitan region in central France centered on the city of Limoges, known historically for its porcelain industry and regional administrative importance.
  • C. Aubusson
    Aubusson is a town in central France renowned for its centuries-old tradition of tapestry and carpet weaving.
  • D. Ville de Moulins
    Ville de Moulins is a French municipal authority that administers the town of Moulins in central France, including cultural sites such as Maison Mantin.
  • E. City of Nancy
    The City of Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed squares.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3e8075a6c8190954d36eb94d1028a completed April 18, 2026, 8:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a013a0b69108190ba3ba6ba7f8d3935 completed May 11, 2026, 2:08 a.m.
Created at: April 10, 2026, 5:35 a.m.