Triple

T8677459
Position Surface form Disambiguated ID Type / Status
Subject Österbottens landskap E205950 entity
Predicate hasNotableCity P2813 FINISHED
Object Jakobstad E266053 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: Jakobstad | Statement: [Österbottens landskap, hasNotableCity, Jakobstad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jakobstad
Context triple: [Österbottens landskap, hasNotableCity, Jakobstad]
  • A. Jakobstad chosen
    Jakobstad is a coastal town and municipality in western Finland known for its bilingual (Finnish and Swedish) heritage and maritime history.
  • B. Vyborg
    Vyborg is a historic port city in northwestern Russia near the Finnish border, known for its medieval castle and long-contested status between Sweden, Finland, and Russia.
  • C. Kotka
    Kotka is a coastal city in southeastern Finland on the Gulf of Finland, known as an important port and maritime center.
  • D. Kajaani
    Kajaani is a small city in central Finland known for its historic castle ruins and role as a regional cultural and economic center in the Kainuu region.
  • E. Uddevalla
    Uddevalla is a coastal town in western Sweden known for its scenic Bohuslän archipelago setting and role as one of the host cities of the 1958 FIFA World Cup.
  • 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_69cf5157c2bc81908b86057779053e64 completed April 3, 2026, 5:34 a.m.
Created at: March 30, 2026, 6:32 p.m.