Triple

T18682528
Position Surface form Disambiguated ID Type / Status
Subject Ebetsu City Government E456770 entity
Predicate jurisdiction P82 FINISHED
Object Ebetsu NE NERFINISHED

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: Ebetsu | Statement: [Ebetsu City Government, jurisdiction, Ebetsu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ebetsu
Context triple: [Ebetsu City Government, jurisdiction, Ebetsu]
  • A. Ebetsu chosen
    Ebetsu is a city in Hokkaido, Japan, known as a suburban and educational hub east of Sapporo.
  • B. Takuu
    Takuu is a remote Polynesian outlier atoll near Papua New Guinea, known for its distinct Polynesian culture and language isolated within Melanesia.
  • C. Sobetsu
    Sobetsu is a small town in Hokkaido, Japan, known for its scenic Lake Tōya views, hot springs, and fruit orchards.
  • D. Karesuando
    Karesuando is a remote village in northern Sweden, situated in the Arctic region near the Finnish border and known as one of the country’s northernmost settlements.
  • E. Otuoke
    Otuoke is a town in Bayelsa State, Nigeria, known as the hometown of former President Goodluck Jonathan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d391eb488190ac2e9abf5bf255e4 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e55b2906ec8190ad8db8e3ae6b2945 completed April 19, 2026, 10:46 p.m.
Created at: April 10, 2026, 11:49 a.m.