Triple

T15292343
Position Surface form Disambiguated ID Type / Status
Subject Gruppo Torinese Trasporti E365557 entity
Predicate hasNetwork P2637 FINISHED
Object Turin Metro Line 1 E74302 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: Turin Metro Line 1 | Statement: [Gruppo Torinese Trasporti, hasNetwork, Turin Metro Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turin Metro Line 1
Context triple: [Gruppo Torinese Trasporti, hasNetwork, Turin Metro Line 1]
  • A. Turin Metro chosen
    The Turin Metro is a fully automated, driverless rapid transit system serving the city of Turin, Italy.
  • B. Genoa Metro Line 1
    Genoa Metro Line 1 is the primary light metro line serving the Italian city of Genoa, connecting key central and suburban areas through an underground rapid transit system.
  • C. Milan Metro Line 1
    Milan Metro Line 1 is the oldest and one of the main rapid transit lines in Milan, Italy, running primarily on an east–west axis and serving key commercial and exhibition areas of the city.
  • D. Brescia Metro
    Brescia Metro is a fully automated light metro system serving the city of Brescia in northern Italy.
  • E. Milan Metro
    The Milan Metro is the rapid transit system serving Milan, Italy, forming the backbone of the city’s public transportation network with multiple underground lines connecting central and suburban areas.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03680b60c8190a3ea54a9d34c8105 completed April 16, 2026, 1:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01e2a03c81909ab24d4ed2b54698 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:15 a.m.