Triple

T3674391
Position Surface form Disambiguated ID Type / Status
Subject Jyväskylä E77953 entity
Predicate hasDistrict P459 FINISHED
Object Vaajakoski
Vaajakoski is a district of the city of Jyväskylä in Central Finland, known for its lakeside setting and industrial history.
E382654 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: Vaajakoski | Statement: [Jyväskylä, hasDistrict, Vaajakoski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vaajakoski
Context triple: [Jyväskylä, hasDistrict, Vaajakoski]
  • A. Taivalkoski
    Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
  • B. Tikkakoski
    Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
  • C. Luumäki
    Luumäki is a rural municipality in South Karelia, southeastern Finland, known for its forests, lakes, and historical significance.
  • D. Vihti
    Vihti is a municipality in southern Finland located within the Uusimaa region, known for its lakes, rural landscapes, and proximity to the Helsinki metropolitan area.
  • E. Lahdenpohja
    Lahdenpohja is a small town in the Ladoga Karelia region of northwestern Russia, situated near the northern shores of Lake Ladoga.
  • 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: Vaajakoski
Triple: [Jyväskylä, hasDistrict, Vaajakoski]
Generated description
Vaajakoski is a district of the city of Jyväskylä in Central Finland, known for its lakeside setting and industrial history.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Vaajakoski
Target entity description: Vaajakoski is a district of the city of Jyväskylä in Central Finland, known for its lakeside setting and industrial history.
  • A. Taivalkoski
    Taivalkoski is a rural municipality in Northern Ostrobothnia, Finland, known for its forests, lakes, and outdoor recreation opportunities.
  • B. Tikkakoski
    Tikkakoski is a district in Jyväskylä, Finland, known for its military air base and role as a key center for the Finnish Air Force.
  • C. Luumäki
    Luumäki is a rural municipality in South Karelia, southeastern Finland, known for its forests, lakes, and historical significance.
  • D. Vihti
    Vihti is a municipality in southern Finland located within the Uusimaa region, known for its lakes, rural landscapes, and proximity to the Helsinki metropolitan area.
  • E. Lahdenpohja
    Lahdenpohja is a small town in the Ladoga Karelia region of northwestern Russia, situated near the northern shores of Lake Ladoga.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc45fbd1c819099023791452f1beb completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4cde628c08190adc058d8d35a5e5d completed March 14, 2026, 2:54 a.m.
NEDg Description generation batch_69b4cf6a84fc8190b07fbc31621bd871 completed March 14, 2026, 3 a.m.
NED2 Entity disambiguation (via description) batch_69b4d32caa7c81908332ac23bd4d9571 completed March 14, 2026, 3:17 a.m.
Created at: March 8, 2026, 3:25 p.m.