Triple

T15463472
Position Surface form Disambiguated ID Type / Status
Subject Operation T E371963 entity
Predicate location P40 FINISHED
Object Tornio E175026 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: Tornio | Statement: [Operation T, location, Tornio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tornio
Context triple: [Operation T, location, Tornio]
  • A. Tornio chosen
    Tornio is a Finnish town located at the northern end of the Gulf of Bothnia, known for its cross-border connection with Sweden and its long history as a trading and industrial center.
  • B. Tornionjoki
    Tornionjoki is a river forming part of the border between Sweden and Finland, known for its salmon fishing and its course into the northern Gulf of Bothnia.
  • C. Seinäjoki River
    Seinäjoki River is a watercourse in western Finland that flows through and gives its name to the city of Seinäjoki.
  • D. Otava River
    The Otava River is a significant river in the Czech Republic that flows through the Bohemian Forest and South Bohemian landscapes before joining the Vltava River.
  • E. Nokianvirta River
    The Nokianvirta River is a waterway in southwestern Finland that flows through the town of Nokia and has historically influenced the region’s settlement and industry.
  • 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_69d85cc8bd308190886949510b42e764 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e03f1927708190a0d2b63e75469a0e completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff365504488190a6f43d82d008c855 completed May 9, 2026, 1:27 p.m.
Created at: April 10, 2026, 3:32 a.m.