Triple

T4526303
Position Surface form Disambiguated ID Type / Status
Subject Montpellier-Méditerranée Airport E106185 entity
Predicate locatedInCountry P40 FINISHED
Object France E861 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: France | Statement: [Montpellier-Méditerranée Airport, locatedInCountry, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [Montpellier-Méditerranée Airport, locatedInCountry, France]
  • A. France chosen
    France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
  • B. Lafrançaise, France
    Lafrançaise is a small commune in the Tarn-et-Garonne department of southern France, known for its rural charm and traditional French village atmosphere.
  • C. France Ô
    France Ô was a French public television channel dedicated to programming from France’s overseas departments and territories, operated by the France Télévisions group.
  • D. France and Germany
    France and Germany are two major neighboring European countries that share deep historical ties, a central role in the European Union, and a long land border.
  • E. France 5
    France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
  • 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_69bd43f3d6e08190a91824f833d51bbe completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd57760f4481908f69ce82be63d7f8 completed March 20, 2026, 2:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda43a82c08190b3d43efcee45a8ea completed March 20, 2026, 7:47 p.m.
Created at: March 20, 2026, 1:03 p.m.