Triple

T15896828
Position Surface form Disambiguated ID Type / Status
Subject Como Lago railway station E385477 entity
Predicate nearTo P350 FINISHED
Object Como city centre E1182940 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: Como city centre | Statement: [Como Lago railway station, nearTo, Como city centre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Como city centre
Context triple: [Como Lago railway station, nearTo, Como city centre]
  • A. Como city center chosen
    Como city center is the historic and commercial heart of the lakeside city of Como in northern Italy, known for its medieval streets, waterfront promenades, and proximity to Lake Como’s main attractions.
  • B. City Centre
    City Centre is Mississauga’s primary downtown core, known for its high-density residential towers, major shopping complexes, and civic and cultural facilities.
  • C. City Centre
    City Centre is the central commercial and cultural district of Cambridge, known for its historic university buildings, shops, and public spaces.
  • D. Innenstadt
    Innenstadt is the central urban district of Frankfurt am Main, known as the city’s historic core and primary commercial area.
  • E. Centrum
    Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15639c9748190b1115f74cbd61330 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5a1b1548190a8579cebf9e71121 completed May 9, 2026, 10:30 p.m.
Created at: April 10, 2026, 4:51 a.m.