Triple

T610643
Position Surface form Disambiguated ID Type / Status
Subject Hokkaido E12089 entity
Predicate capital P234 FINISHED
Object Sapporo E40366 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: Sapporo | Statement: [Hokkaido, capital, Sapporo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sapporo
Context triple: [Hokkaido, capital, Sapporo]
  • A. Sapporo chosen
    Sapporo is the capital and largest city of Japan’s northern Hokkaido prefecture, known for its annual snow festival, beer, and ski resorts.
  • B. Hakodate
    Hakodate is a historic port city on Japan’s northern island of Hokkaido, known for its scenic night views from Mount Hakodate and its blend of Japanese and Western-influenced architecture.
  • C. Niigata
    Niigata is a major coastal city in north-central Japan known for its important seaport on the Sea of Japan, rice production, and sake brewing.
  • D. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • E. Sendai
    Sendai is the largest city in Japan’s Tōhoku region, known for its lush greenery, historic sites, and status as a major economic and cultural center in northeastern Honshu.
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49df7c088819082eb70de4f0f4fbf completed March 1, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69af1731ebe481908ffd1a670ae86286 completed March 9, 2026, 6:53 p.m.
Created at: March 1, 2026, 7:35 p.m.