Triple

T525489
Position Surface form Disambiguated ID Type / Status
Subject Paris Orly Airport E10907 entity
Predicate locatedIn P40 FINISHED
Object Paris metropolitan area E76769 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: Paris metropolitan area | Statement: [Paris Orly Airport, locatedIn, Paris metropolitan area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris metropolitan area
Context triple: [Paris Orly Airport, locatedIn, Paris metropolitan area]
  • A. Grand Paris urban area chosen
    The Grand Paris urban area is the large metropolitan region centered on Paris that encompasses the city and its surrounding suburbs and commuter towns.
  • B. Metropolitan France
    Metropolitan France is the part of France located in Europe, encompassing the mainland and nearby coastal islands, and forming the country’s primary political, economic, and demographic center.
  • C. Paris
    Paris is the capital and largest city of France, renowned for its historic architecture, art, fashion, and cultural influence worldwide.
  • D. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • E. Saint-Germain-en-Laye
    Saint-Germain-en-Laye is a historic town in the western suburbs of Paris, France, known for its royal château and long association with the French monarchy.
  • 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_69a2e84b16c4819088d284c47c3a7968 completed Feb. 28, 2026, 1:06 p.m.
NER Named-entity recognition batch_69a2f1b7f448819087e5e7f3b37d7142 completed Feb. 28, 2026, 1:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69a55544eda481908fae6a9f77ff9d97 completed March 2, 2026, 9:15 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.