Triple

T11287383
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 13 E267231 entity
Predicate hasInterchangeStation P2413 FINISHED
Object Miromesnil E414196 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: Miromesnil | Statement: [Paris Métro Line 13, hasInterchangeStation, Miromesnil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Miromesnil
Context triple: [Paris Métro Line 13, hasInterchangeStation, Miromesnil]
  • A. Miromesnil chosen
    Miromesnil is a Paris Métro station in the 8th arrondissement, serving as an interchange between lines 9 and 13 near the Élysée Palace.
  • B. Orgeval
    Orgeval is a district in the city of Reims, France, known in part for serving as a terminus of the Reims tramway network.
  • C. Magnicourt
    Magnicourt is a small French commune located in the Aube department in the Grand Est region of northeastern France.
  • D. Chamrousse
    Chamrousse is a French alpine ski resort and mountain commune in the Alps, known for its winter sports facilities and scenic high-altitude landscapes.
  • E. Tiffauges
    Tiffauges is a historic commune in western France, known for its medieval castle and scenic setting along the Sèvre Nantaise river.
  • 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_69d6aac993a08190a6f36445ebaf9a43 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e986b0f08190a414749eaa7f1a5d completed April 9, 2026, 6:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69e50a18ef88819095905fe726e07053 completed April 19, 2026, 5 p.m.
Created at: April 8, 2026, 9:32 p.m.