Triple

T15382211
Position Surface form Disambiguated ID Type / Status
Subject Milan Metro Line 2 E367831 entity
Predicate hasTerminus P388 FINISHED
Object Cologno Nord E805187 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: Cologno Nord | Statement: [Milan Metro Line 2, hasTerminus, Cologno Nord]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cologno Nord
Context triple: [Milan Metro Line 2, hasTerminus, Cologno Nord]
  • A. Cologno Monzese chosen
    Cologno Monzese is a suburban town in northern Italy known for hosting major television and media studios near Milan.
  • B. Collegno
    Collegno is a municipality in the Metropolitan City of Turin in northern Italy, known as a residential and industrial suburb of Turin.
  • C. Norcino
    Norcino is the Italian demonym for a person from Norcia, a town in the Umbria region of central Italy.
  • D. Calusco d’Adda
    Calusco d’Adda is a municipality in the Province of Bergamo in Lombardy, northern Italy, situated along the Adda River.
  • E. Sarnico
    Sarnico is a picturesque town in northern Italy known as a lakeside resort and boating center on the southern shore of Lake Iseo.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e61928c81908852c355d537ed9c completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff0b5bc43c81908ffdb7819e3660d9 completed May 9, 2026, 10:24 a.m.
Created at: April 10, 2026, 3:19 a.m.