Triple

T525533
Position Surface form Disambiguated ID Type / Status
Subject Paris Orly Airport E10907 entity
Predicate locatedInDepartment P40 FINISHED
Object Essonne E45084 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: Essonne | Statement: [Paris Orly Airport, locatedInDepartment, Essonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Essonne
Context triple: [Paris Orly Airport, locatedInDepartment, Essonne]
  • A. Essonne chosen
    Essonne is a department in northern France that forms part of the Paris metropolitan region and includes a mix of suburban communities, research centers, and rural areas.
  • B. Seine-et-Marne
    Seine-et-Marne is a largely rural department in north-central France east of Paris, known for its historic towns, agricultural landscapes, and attractions such as the Château de Fontainebleau and Disneyland Paris.
  • C. Sarthe
    Sarthe is a river in western France that flows through the regions of Normandy and Pays de la Loire before joining other waterways to form the Loire basin.
  • D. Yvelines
    Yvelines is a department in north-central France, west of Paris, known for the Palace of Versailles and its mix of historic towns, forests, and affluent suburbs.
  • E. Val-de-Marne
    Val-de-Marne is a suburban department in north-central France, southeast of Paris, known for its mix of residential communities, river landscapes along the Marne, and key transport links within the Île-de-France region.
  • 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_69a2f3b7557c8190a29cf1de359ea2ea completed Feb. 28, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69a50e1f11c08190a0fb6198ca7b61e8 completed March 2, 2026, 4:12 a.m.
Created at: Feb. 28, 2026, 1:12 p.m.