Triple

T2984607
Position Surface form Disambiguated ID Type / Status
Subject Muroran E80590 entity
Predicate hasSymbol P129 FINISHED
Object Muroran city flag E80590 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: Muroran city flag | Statement: [Muroran, hasSymbol, Muroran city flag]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Muroran city flag
Context triple: [Muroran, hasSymbol, Muroran city flag]
  • A. Muroran chosen
    Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
  • B. Petrozavodsk, Russia
    Petrozavodsk is the capital city of Russia’s Republic of Karelia, located on the western shore of Lake Onega and known as a regional cultural and industrial center.
  • C. Furano
    Furano is a popular town in central Hokkaido, Japan, known for its scenic ski slopes in winter and vibrant lavender fields in summer.
  • D. Krasnoyarsk, Russia
    Krasnoyarsk is a major industrial and cultural city in central Siberia, Russia, situated on the Yenisei River and known as a key hub of the region.
  • E. Odintsovo
    Odintsovo is a town in western Russia that serves as an important suburban center just outside Moscow.
  • 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_69ad8b16c3488190b47b6aa7a59a335b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad99c65ad0819087bb4ae92ab0dc55 completed March 8, 2026, 3:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b108f8b2b08190904cf89befe656dd completed March 11, 2026, 6:17 a.m.
Created at: March 8, 2026, 2:59 p.m.