Triple

T17011509
Position Surface form Disambiguated ID Type / Status
Subject M1 line E412710 entity
Predicate hasStation P35 FINISHED
Object Siilitie station
Siilitie station is a metro station in Helsinki, Finland, serving the city’s M1 line.
 E1253492 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: Siilitie station | Statement: [M1 line, hasStation, Siilitie station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Siilitie station
Context triple: [M1 line, hasStation, Siilitie station]
  • A. Matinkylä station
    Matinkylä station is a metro station in the Espoo district of Matinkylä that serves as a key western endpoint of the Helsinki Metro system.
  • B. 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.
  • C. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • D. 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.
  • E. Kulosaari station
    Kulosaari station is a Helsinki Metro station serving the Kulosaari island district in eastern Helsinki, Finland.
  • 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: Siilitie station
Triple: [M1 line, hasStation, Siilitie station]
Generated description
Siilitie station is a metro station in Helsinki, Finland, serving the city’s M1 line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Siilitie station
Target entity description: Siilitie station is a metro station in Helsinki, Finland, serving the city’s M1 line.
  • A. Matinkylä station
    Matinkylä station is a metro station in the Espoo district of Matinkylä that serves as a key western endpoint of the Helsinki Metro system.
  • B. 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.
  • C. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • D. 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.
  • E. Kulosaari station
    Kulosaari station is a Helsinki Metro station serving the Kulosaari island district in eastern Helsinki, Finland.
  • 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_6a0148222034819089474594ee351b05 completed May 11, 2026, 3:08 a.m.
NEDg Description generation batch_6a0148a0a9e48190ab588c0e33784048 completed May 11, 2026, 3:10 a.m.
NED2 Entity disambiguation (via description) batch_6a0149262a0c8190b52842181bea6d59 completed May 11, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:33 a.m.