Triple

T15425777
Position Surface form Disambiguated ID Type / Status
Subject Tramway T12 Express E369504 entity
Predicate regionServed P82 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: [Tramway T12 Express, regionServed, Essonne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Essonne
Context triple: [Tramway T12 Express, regionServed, 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-Oise
    Seine-et-Oise was a former department of France surrounding Paris, abolished in 1968 and divided into several new departments including Yvelines.
  • C. Loir-et-Cher
    Loir-et-Cher is a department in central France known for its historic châteaux, including parts of the Loire Valley UNESCO World Heritage site.
  • D. Eure-et-Loir
    Eure-et-Loir is a department in north-central France, located in the Centre-Val de Loire region and known for including the historic city of Chartres.
  • E. 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.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ec1fb288190a3625b8e4f487dd1 completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff2cf5d788819086a94af42c2ec21a completed May 9, 2026, 12:47 p.m.
Created at: April 10, 2026, 3:20 a.m.