Triple

T17011512
Position Surface form Disambiguated ID Type / Status
Subject M1 line E412710 entity
Predicate hasStation P35 FINISHED
Object Kontula station
Kontula station is an eastern Helsinki metro station serving the Kontula district on the city’s rapid transit network.
E1257962 NE FINISHED

How this triple was built (4 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: Kontula station | Statement: [M1 line, hasStation, Kontula station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kontula station
Context triple: [M1 line, hasStation, Kontula station]
  • A. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • B. Herttoniemi station
    Herttoniemi station is a metro station in the Herttoniemi district of Helsinki, Finland, serving as part of the city’s rapid transit network.
  • C. Kulosaari station
    Kulosaari station is a Helsinki Metro station serving the Kulosaari island district in eastern Helsinki, Finland.
  • D. Sörnäinen station
    Sörnäinen station is an underground metro station in Helsinki, Finland, serving the densely populated Sörnäinen and Kallio districts on the city’s metro network.
  • E. Käppala station
    Käppala station is a stop on Stockholm’s Lidingöbanan light rail line serving the Käppala area on the island of Lidingö, Sweden.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kontula station
Triple: [M1 line, hasStation, Kontula station]
Generated description
Kontula station is an eastern Helsinki metro station serving the Kontula district on the city’s rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kontula station
Target entity description: Kontula station is an eastern Helsinki metro station serving the Kontula district on the city’s rapid transit network.
  • A. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • B. Herttoniemi station
    Herttoniemi station is a metro station in the Herttoniemi district of Helsinki, Finland, serving as part of the city’s rapid transit network.
  • C. Kulosaari station
    Kulosaari station is a Helsinki Metro station serving the Kulosaari island district in eastern Helsinki, Finland.
  • D. Sörnäinen station
    Sörnäinen station is an underground metro station in Helsinki, Finland, serving the densely populated Sörnäinen and Kallio districts on the city’s metro network.
  • E. Käppala station
    Käppala station is a stop on Stockholm’s Lidingöbanan light rail line serving the Käppala area on the island of Lidingö, Sweden.
  • F. None of above. chosen

Provenance (5 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d47cc17c819087f7bd27582bcbfa completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01673e1be08190b39c38fd8115a02c completed May 11, 2026, 5:21 a.m.
NEDg Description generation batch_6a0168a45fc881908540d142db1ed1e9 completed May 11, 2026, 5:27 a.m.
NED2 Entity disambiguation (via description) batch_6a01692c44c881908cd986ad6cf10596 completed May 11, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:33 a.m.