Triple

T20239501
Position Surface form Disambiguated ID Type / Status
Subject Lake Päijänne E498243 entity
Predicate hasTownOnShore P969 FINISHED
Object Padasjoki E1196156 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: Padasjoki | Statement: [Lake Päijänne, hasTownOnShore, Padasjoki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Padasjoki
Context triple: [Lake Päijänne, hasTownOnShore, Padasjoki]
  • A. Padasjoki chosen
    Padasjoki is a small municipality in southern Finland known for its lakeside landscapes and outdoor recreation opportunities.
  • B. Kalajoki
    Kalajoki is a coastal town and municipality in Northern Ostrobothnia, Finland, known for its long sandy beaches and tourism.
  • C. Kajansi
    Kajansi is a township in Uganda located near Kampala, known for its strategic position along the Kampala–Entebbe road and its local market and trading activities.
  • D. Kilpisjärvi
    Kilpisjärvi is a remote village in northwestern Finnish Lapland, near the borders with Sweden and Norway, known for its Arctic landscapes, hiking opportunities, and proximity to the Saana fell.
  • E. Kangasala
    Kangasala is a Finnish town and municipality in the Pirkanmaa region, known for its scenic ridge landscapes and lakes.
  • 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6716dd0b081909d4063150cdc0c02 completed April 20, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0a735b9e5881909ec8672fd82c1068 completed May 18, 2026, 2:03 a.m.
Created at: April 11, 2026, 11:40 p.m.