Triple

T17011508
Position Surface form Disambiguated ID Type / Status
Subject M1 line E412710 entity
Predicate hasStation P35 FINISHED
Object 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.
E1252667 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: Herttoniemi station | Statement: [M1 line, hasStation, Herttoniemi station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Herttoniemi station
Context triple: [M1 line, hasStation, Herttoniemi 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. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • C. Käppala station
    Käppala station is a stop on Stockholm’s Lidingöbanan light rail line serving the Käppala area on the island of Lidingö, Sweden.
  • D. Vuosaari station
    Vuosaari station is an eastern Helsinki Metro station serving the Vuosaari district as one of the line’s terminal endpoints.
  • E. Mellunmäki station
    Mellunmäki station is an eastern Helsinki Metro station in the Mellunmäki district, notable for being one of the metro system’s outermost endpoints.
  • 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: Herttoniemi station
Triple: [M1 line, hasStation, Herttoniemi station]
Generated description
Herttoniemi station is a metro station in the Herttoniemi district of Helsinki, Finland, serving as part of the city’s rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Herttoniemi station
Target entity description: Herttoniemi station is a metro station in the Herttoniemi district of Helsinki, Finland, serving as part of the city’s rapid transit network.
  • 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. Kivenlahti station
    Kivenlahti station is a western endpoint of the Helsinki Metro system serving the Kivenlahti district in Espoo, Finland.
  • C. Käppala station
    Käppala station is a stop on Stockholm’s Lidingöbanan light rail line serving the Käppala area on the island of Lidingö, Sweden.
  • D. Vuosaari station
    Vuosaari station is an eastern Helsinki Metro station serving the Vuosaari district as one of the line’s terminal endpoints.
  • E. Mellunmäki station
    Mellunmäki station is an eastern Helsinki Metro station in the Mellunmäki district, notable for being one of the metro system’s outermost endpoints.
  • 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_6a01413cc6f08190ae83a0c98fb96b90 completed May 11, 2026, 2:38 a.m.
NEDg Description generation batch_6a014218d0cc81909c1b1b4c11484364 completed May 11, 2026, 2:42 a.m.
NED2 Entity disambiguation (via description) batch_6a01427ce5d08190b383ea907ca3352e completed May 11, 2026, 2:44 a.m.
Created at: April 10, 2026, 5:33 a.m.