Triple

T8677436
Position Surface form Disambiguated ID Type / Status
Subject Österbottens landskap E205950 entity
Predicate containsMunicipality P852 FINISHED
Object Isokyrö E205953 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: Isokyrö | Statement: [Österbottens landskap, containsMunicipality, Isokyrö]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isokyrö
Context triple: [Österbottens landskap, containsMunicipality, Isokyrö]
  • A. Isokyrö chosen
    Isokyrö is a rural municipality in western Finland known for its historic churches, agricultural landscape, and traditional Ostrobothnian culture.
  • B. Raisio
    Raisio is a town and municipality in southwestern Finland known for its industrial base and as the headquarters of the food company Raisio Group.
  • C. Kauhava
    Kauhava is a town in western Finland known historically for its aviation activities and air base, as well as its traditional knife-making heritage.
  • D. Tuompo
    Tuompo is a Finnish surname associated with individuals such as Wiljo Tuompo.
  • E. Kagermeer
    Kagermeer is a lake in the Kagerplassen lake district in South Holland, Netherlands, popular for boating and watersports.
  • 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_69ca83529a9c8190b5c075b4f14636ed completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc49f7c2c081909ec93413ceefbb1c completed March 31, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3a008d48190bd0e58f615eda148 completed April 2, 2026, 10:54 p.m.
Created at: March 30, 2026, 6:32 p.m.